Reviewerly/exHarmony huggingface dataset:
Pengembangan Multimedia Interaktif untuk Diklat Tenaga Prawatan Listrik Aliran atas di BPTP Sofyan Hadi

This research aims to produce a product in the form of interactive multimedia that will be used as one of the supporting media of learning for the training of railway infrastructure maintenance personnel namely upper flow electricity in Sofyan Hadi Railway Engineering Training Center. In this development research, the development model used refers to the R&amp;D (Research and Development) method by thiagarajan developed 4D development models that have stages consisting of: Define, Design, Develop, and Disseminate. Products developed from this study have gone through formative evaluation stages including Expert Review, One to One, and large-scale trials.The results of the Expert Review from learning media experts get a score of 3.80 (Excellent).The material expert gets a value of 3.70 (Excellent). One to One trial results get 3.60 (Excellent) results. Large-scale trial results get 3.60 (Excellent) results. Based on these results, it can be concluded that the Interactive Multimedia product for the Overhead Catenary Engineering Training is expressed very well.
Collaborative Filtering with Smooth Reconstruction of the Preference Function

The problem of predicting the rating of a set of users to a set of items in a recommender system based on partial knowledge of the ratings is widely known as collaborative filtering. In this paper, we consider a mapping of the items into a vector space and study the prediction problem by assuming an underlying smooth preference function for each user, the quantization at each given vector yields the associated rating. To estimate the preference functions, we implicitly cluster the users with similar ratings to form dominant types. Next, we associate each dominant type with a smooth preference function; i.e., the function values for items with nearby vectors shall be close to each other. The latter is accomplished by a rich representation learning in a so-called frequency domain. In this framework, we propose two approaches for learning user and item representations. First, we use an alternating optimization method in the spirit of k-means to cluster users and map items. We further make this approach less prone to overfitting by a boosting technique. Second, we present a feedforward neural network architecture consisting of interpretable layers which implicitely clusters the users. The performance of the method is evaluated on two benchmark datasets (ML-100k and ML-1M). Albeit the method benefits from simplicity, it shows a remarkable performance and opens a venue for future research. All codes are publicly available on the GitLab.
Approach to Remote Teaching for Mechanical Engineering Curriculum at COVID-19

We had to try Remote Teaching the cause of COVID-19 I tried to Remote Teaching for Mechanical Engineering This Trying was many ways This result states the effect for students of Remote Teaching for Mechanical Engineering
Quantitative Comparative Study of Video Denoising with Optical Flow Estimation in Spatial and Transform Domains

In this paper we establish an extensive quantitative comparative study of patch-based video denoising with optical flow estimation algorithms. Namely, SPTWO, VBM3D and VBM4D algorithms are considered. The aim of this study is to combine these video denoising algorithms in a hybrid proposed process to take advantage of. SPTWO takes advantage of the self-similarity and redundancy of adjacent frames. The proposed hybrid algorithm and the three video denoising algorithms are implemented and tested on real sequences degraded by various level Additive White Gaussian Noise (AWGN). The obtained results are compared in terms of the most used performance criteria for various test cases. The performance criteria computed in this study are: RMSE and SSIM in addition to the running time and visual quality of the sequence video. Experimental results, illustrate that the proposed algorithm and SPTWO provide the best video quality and appear to be efficient in terms of preserving fine texture and detail reconstruction.
INVESTIGATING THE DIGITAL READINESS FOR ACADEMIC ENGAGEMENT OF INTERNATIONAL UNIVERSITY STUDENTS

The purpose this study was to investigate digital readiness of university students for academic engagement. It was conducted at Gaziantep University on international students from Africa, America, Asia and European continents studying at different faculties, levels and years. A quantitative descriptive survey involved 288 international students (64.2% male and 35.8% female) selected using simple random sampling technique. The questionnaire instrument contained 17 items which were derived from Hung and Kim (2018) DRAE scale.The findings revealed that to a large extent the international university students are ready for the digital technologies’ utilization in the academic field. Despite the fact that there were some deficiencies at the digital media awareness and digital tool application subscales. The findings showed that there were significant differences (p≤0.05) in participant’s gender, geographical region, year, level and faculty of study groups. The researcher recommended provision of extra digital technology related lessons to students, political stability in the Middle East region and access to digital technology by students at high school to prepare them their usage at university level.
Supporting Disadvantaged Multilingual Families in Using Their Own Resources in Education

For decades, researchers, policy makers and education practitioners have been trying to eliminate inequality in education throughout the stages of education and across the globe. The research so far proves that the early stages of development are crucial and that it is never too soon to start with support and interventions. Nevertheless, the younger the child, the more conflicting with the domestic environment the interventions may appear. Therefore, it is becoming crucial to understand the cultural background on the side of the families in order to set up successful mechanisms that might help to fill the education gaps, ideally engaging the caretakers themselves in taking effective action. At the same time, the school-attending children of these days are now, at least in Europe, fully digitalized from the moment of their birth, so it is only natural to consider virtual learning environments as an essential part of the education innovations that might help tackle social inequalities. However, digitalization is not an automatic solution to educational inequalities: it may be quite the contrary if the social and cultural background of its users is not treated with proper regard.
QoS-Aware Dynamical Resource Scheduling in Cloud Data Centers

In order to improve the utilization rate of cloud computing resources within the data center, the scheduler dynamically allocates resources according to the load of each node and migrates virtual machines. Virtual machine migration is one of the effective ways to realize the dynamic allocation of resources, and virtual machine migration will cause a certain quality of service interference to the services carried on it. We analyze the impact of virtual machine migration on service quality, study the problems of virtual machine migration timing, migration objects and migration destination, targeted optimization strategies, established an evaluation model of the impact of migration mechanism on service quality. Based on this, an effective dynamic resource scheduling strategy is proposed. Experimental results show that compared with the existing online migration strategy, our model can reduce unnecessary migration by about 33% on average while reducing migration costs by 30%. In addition, our proposed resource scheduling strategy solves the problem of insufficient resources during the subsequent migration of a heavily loaded virtual machine.
Unlabeled Data Guided Semi-supervised Histopathology Image Segmentation

Automatic histopathology image segmentation is crucial to disease analysis. Limited available labeled data hinders the generalizability of trained models under the fully supervised setting. Semi-supervised learning (SSL) based on generative methods has been proven to be effective in utilizing diverse image characteristics. However, it has not been well explored what kinds of generated images would be more useful for model training and how to use such images. In this paper, we propose a new data guided generative method for histopathology image segmentation by leveraging the unlabeled data distributions. First, we design an image generation module. Image content and style are disentangled and embedded in a clustering-friendly space to utilize their distributions. New images are synthesized by sampling and cross-combining contents and styles. Second, we devise an effective data selection policy for judiciously sampling the generated images: (1) to make the generated training set better cover the dataset, the clusters that are underrepresented in the original training set are covered more; (2) to make the training process more effective, we identify and oversample the images of “hard cases” in the data for which annotated training data may be scarce. Our method is evaluated on glands and nuclei datasets. We show that under both the inductive and transductive settings, our SSL method consistently boosts the performance of common segmentation models and attains state-of-the-art results.
Visual Analytics on Public Grievance Data using Tableau

Every year Centralized Public Grievance Redress and Monitoring System (CPGRMS) records and monitors the total number of grievances registered and the number of pending or disposed grievances out of the total number received. As per CPGRMS reports, every year only 80% of the total registered grievances are resolved and disposed and the remaining 20% stays pending. Since there exist huge amount of data related to pending cases, a mechanism needs to devised to address the issues. Data visualization from analytical from of view can be provided with the help of Tableau. It can assist in providing quick and handy information. Tableau facilitates a vast variety of visualization fields and topics. In this paper an attempt has been made to analyze the grievance data from 2016-19 related to ministries with the maximum and the minimum number of pending grievances, along with predicting and deciding the department(s) requiring the foremost concern so as to avoid any further delay in the disposal of the registered grievances.
LibGuides: LibWizard Tutorials for Classroom Use: Tutorial Links

A collection of tutorials created by Trustee Library librarians to help students with research and writing.
A New Discretization Approach of Bat and K-Means

Bat algorithm is one of the optimization techniques that mimic the behavior of bat.Bat algorithm is a powerful algorithm in finding the optimum feature data collection.Classification is one of the data mining tasks that useful in knowledge representation.But, the high dimensional data become the issue in the classification that interrupt classification accuracy.From the literature, feature selection and discretization able to overcome the problem.Therefore, this study aims to show Bat algorithm is potential as a discretization approach and as a feature selection to improve classification accuracy.In this paper, a new hybrid Bat-K-Mean algorithm refer as hBA is proposed to convert continuous data into discrete data called as optimize discrete dataset.Then, Bat is used as feature selection to select the optimum feature from the optimized discrete dataset in order to reduce the dimension of data.The experiment is conducted by using k-Nearest Neighbor to evaluate the effectiveness of discretization and feature selection in classification by comparing with continuous dataset without feature selection, discrete dataset without feature selection, and continuous dataset without discretization and feature selection.Also, to show Bat is potential as a discretization approach and feature selection method. .The experiments were carried out using a number of benchmark datasets from the UCI machine learning repository.The results show the classification accuracy is improved with the Bat-K-Means optimized discretization and Bat optimized feature selection.
LibGuides: Library Tutorial Videos: Overview

These very short video tutorials will help you to search the library website, the library catalog, and the various databases that the library provides access to.
Establish efficient portofolio on LQ45 index using stochastic dominance

Investing on stock aims to get returns in the future. Stock as one of the risky investment need to be anticipated by selecting strong stock to form portofolio. Efficient portofolio can be established from dominant stocks on LQ45 Index. The purpose of this research is to apply SD method in forming efficient portofolio on LQ45 Index. The criteria used historical data on stock returns and showed which one dominates the other one. The monthly closing stock price of LQ45 Index were taken over the period of February 2016 until January 2020. The results show that there are 1 dominance in FSD, 84 dominance in SSD, and 41 dominance in TSD. The efficient portofolio obtained from ADRO, ASII, BBCA, BBNI, BBRI, BMRI, ICBP, INDF, KLBF, SMGR, TLKM, and UNTR. Furthermore, it can be concluded that the returns expectations of portofolio is 0.01196 and the risk level of portofolio is 0.0295.
Research Guides: eBooks: Getting Started

Provides resources that contain eBooks. If unsure where to start, or need help, please ask a librarian for help.
Kompetensi Dakwah Dan Praktek Safari Romadlon Santri Darussalam Sumbersari Kencong Kepung Kediri

This study concerns the competence of da'wah and Romadlon safari practices which are specifically directed at santri in the Islamic Boarding School of Sumbersari Kencong Kepung, Kediri Regency relating to the plunge of students studying in the community for nasyrul ilmi waddin related to da'wah which is manifested in the form of safari Romadlon. This type of research approach is qualitative phenomenological, with a case study design. Data collection is done by in-depth interview techniques, observation, and study documentation. While the data analysis technique, researchers used an interactive analysis model that contained four interrelated components, namely: data collection, data simplification, data exposure, withdrawal and submission of conclusions. Finally, this study managed to obtain findings in accordance with the problem questions which in general can be concluded as follows: 1). Da'wah planning implemented at Darussalam Sumbersari Islamic boarding school in general can be said to be good which includes training, screening of all Romadlon safari participants so that safari activities can go well, 2). Romadlon safari practices by recording areas that will be occupied by the students went well, 3). Santri who was deployed assisted by the Romadlon safari committee was felt to be able to overcome the existing problems both internally and externally.
Bitcoins as a determinant of stock market movements: A comparison of Indian and Chinese Stock Markets

The present paper aims to examine the relationship between price movement of cryptocurrency (Bitcoin) and stock exchange movements of two major global economies i.e. India and China. 1133 number of observations on daily basis were taken from 1st January 2015 to 29th November 2019 and analysed using statistical software E-views. Statistical techniques like Granger Causality, Johnsen Co-integration and VECM have been employed to achieve the objective of the paper. The empirical results of the paper depict that long run relationship exists between Bitcoin and stock exchanges of India and China. Sensex has the unidirectional causality with Bitcoin. The significant t-statistics imply an influential role of Sensex in Bitcoin price movement. The results further indicate that there is no evidence of any causal relationship between Bitcoin and Chinese Stock exchange, which suggests a better risk-return mechanism for the global investors and policy makers. The findings of the paper can be imparted as guidelines for the global investors for diversifying their portfolios.
Black Magic in Deep Learning: How Human Skill Impacts Network Training.

How does a user's prior experience with deep learning impact accuracy? We present an initial study based on 31 participants with different levels of experience. Their task is to perform hyperparameter optimization for a given deep learning architecture. The results show a strong positive correlation between the participant's experience and the final performance. They additionally indicate that an experienced participant finds better solutions using fewer resources on average. The data suggests furthermore that participants with no prior experience follow random strategies in their pursuit of optimal hyperparameters. Our study investigates the subjective human factor in comparisons of state of the art results and scientific reproducibility in deep learning.
An Approach to the Exact Packed String Matching Problem

Searching data is a natural behavior of humankind and is also a fundamental operation in both industrial and academic areas. There has been research into developing sophisticated methods and techniques for string searching. The common method is to make use of prefixes and suffixes to move through the text while searching a string query in a text. It suffers from high computational complexity since it has to repeatedly search each character in the string query sequentially. In this paper, we address the difficulty and propose a novel approach that enables a parallel search of the text without indexing the text or the query which is needed for sequential search. The proposed approach utilizes an XNOR operation in conjunction with the shift method to find the instance of a query. We validated it through experiments finding improvement against other methods.
Use Awareness of ICT enabled Information Services: A Comparative Study

The authors conducted the user awareness study of Information and Communication Technology (ICT) enabled information services facilitated by the university libraries. It was a comparative study of deemed university libraries of Delhi; NCR (National Capital Region). NIRF 2017 of MHRD was used to select the deemed universities for the study. The primary data were collected through the content analysis of the websites and the survey of the libraries using a structured questionnaire. The Five ICT enabled information services were selected taking into consideration the point of view of the users towards the services. Through a well-structured questionnaire data were collected in three categories: ‘Aware and useful’, ‘Aware but not useful’ and ‘Not aware’. The collected data were analysed through the simple percentage calculation method. The study revealed that overall 84.4% of users were ‘aware’ of the ICT enabled information services selected for the study. The study also provided a brief overview of the patron’s perception of the usefulness of the studied services. 61.3% of the users found these services useful to them in accessing the university library resources.
Surprise skills of your smart speaker

Don't let your smart speaker be smarter than you. Consumer Reports has expert advice to make sure you're using your smart speaker to your advantage.
Altering the Home Literacy Environment: A Look into How Teachers are Supporting Families Through Home Literacy Interventions

This empirical research study investigated the following two research questions: what are kindergarten, first and second-grade teachers currently using to make improvements to the home literacy environments of their students and what supports are teachers providing to families of their students to make these improvements successful. In this study, nine elementary teachers were surveyed. An online survey containing qualitative and quantitative questions was used. The first finding from this research study was that teachers are currently provided families with literacy resources/activities to complete at home with their child/children. The second finding for this research study was that teachers stated that it would be possible to positively influence the home literacy environments of their students but they needed more literacy resources in order to adequately support their students’ literacy learning at home. The third finding was that the participants were confident in their ability to support families with home literacy practices and were knowledgeable about the most effective home literacy practices that families could use. The findings from this research study showed that kindergarten, first and second-grade teachers were supporting the home literacy environments and the families of their students by sending home literacy resources.
LibGuides: Security Tools: Encryption and Security Certificates: Sharing Your Public Key

First in a series on security tools, this guide discusses encryption, security certificates, and Public Key Infrastructure
LibGuides: On The Move: Mobile Library Innovations: BookMobiles

Mobile Libraries have been around since the beginning of libraries in the United States, different communities sourced books on horseback, by train, by bus, by bicycle, and automobiles.
USING JIGSAW TECHNIQUE TO IMPROVE STUDENTS’ READING COMPREHENSION IN DESCRIPTIVE TEXT

Reading plays an important role in learning process because it gives knowledge, information, and idea to be applied in the speaking and writing. But, the students of class VII B in the 2017/2018 year of SMP Negeri 1 Pohjentrek had difficulties in comprehending the descriptive text they read. Therefore, the researcher used Jigsaw technique to improve their comprehension in reading descriptive text. This research used collaborative classroom action research design. The aim of this research was to improve the students’ reading comprehension in descriptive text. The successful of this research could be seen by the students’ involvement in the class, the result of questionnaire and the result of the test. The result of the students’ involvement, the questionnaire and the test always improve in every meeting. The conclusion of the research was using Jigsaw technique could improve the students’ reading comprehension in descriptive text. The implementation of using Jigsaw technique also helped the students in comprehending the text, answering the question correctly and improving the students’ reading ability. The English teacher has to have a new way or technique in teaching reading and it will give a motivation for the students to improve their reading comprehension. Keywords : Jigsaw, Reading Comprehension, Descriptive Text
Rancang Bangun Sistem Informasi Akuntansi Penjualan dan Pembelian Pada Koperasi Karyawan Senayan City Jakarta Menggunakan Metode Waterfall

The Senayan City Employee Cooperative is a cooperative that operates in the field of savings and loans and at the same time manages a shop business unit, buying and selling transactions are only recorded in Microsoft Excel format, when sales transactions are not immediately recorded so mistakes often occur. For this reason, we designed a sales and purchase information system design at the Senayan City Employee Cooperative using desktop-based java NetBeans, with the aim of creating a computerized system so that it could be used by the cooperative management. The software development methodology used in this research includes software requirements analysis, design, code generation, testing, and support. The results obtained from this research are the need for a cash sales accounting information system, cash receipts and sales reports that can assist cooperative managers in making decisions
Creation of the Multimedia Electronic Information on Educational Resources

The paper discusses technologies for creating multimedia electronic information, educationalresources for educational institutions.