Reviewerly/exHarmony huggingface dataset:
Pengembangan Bahan Ajar Digital Interaktif Berbantuan Adobe Flash Pada Mata Pelajaran Korespondensi Kelas X OTKP di SMK YPM 3 Taman

The development of digital interactive media assisted with adobe flash research is done to describe the result of the development of that media, its appropriateness which is observed based on the subject expert validator, graphics, language, and the responses of the students toward the media. This research is applied on the understanding basic competence of the office communication and applying communication using phone in Indonesia language as learning media for the students of tenth grade of OTKP 1 in YPM 3 Taman Vocational high school on correspondence subject. This thesis uses developments research (R&amp;D) with the 4-D development model which is about 4 steps of research, they are Defining, arranging, developing, and spreading process. However, the subjects of this research are 20 students of tenth graders in YPM 3 Taman vocational high school. The result of this research shows that interactive digital media is absolutely suitable for teaching. It is 97% for material validation feasibility (very good), 97% for graphic feasibility (very good), 98% for language feasibility (excellent). The average of the result is 97,3%, which means excellent. While the result of the students response is 98,8%, which means excellently interpreted. Based on the result, it is concluded that the interactive digital media, assisted with adobe flash, on the correspondence subject is suitable and good for being applied as both a media and learning source for the students in teaching-learning process.
Measuring Arithmetic Extrapolation Performance

The Neural Arithmetic Logic Unit (NALU) is a neural network layer that can learn exact arithmetic operations between the elements of a hidden state. The goal of NALU is to learn perfect extrapolation, which requires learning the exact underlying logic of an unknown arithmetic problem. Evaluating the performance of the NALU is non-trivial as one arithmetic problem might have many solutions. As a consequence, single-instance MSE has been used to evaluate and compare performance between models. However, it can be hard to interpret what magnitude of MSE represents a correct solution and models sensitivity to initialization. We propose using a success-criterion to measure if and when a model converges. Using a success-criterion we can summarize success-rate over many initialization seeds and calculate confidence intervals. We contribute a generalized version of the previous arithmetic benchmark to measure models sensitivity under different conditions. This is, to our knowledge, the first extensive evaluation with respect to convergence of the NALU and its sub-units. Using a success-criterion to summarize 4800 experiments we find that consistently learning arithmetic extrapolation is challenging, in particular for multiplication.
Deteksi Twitter Bot menggunakan Klasifikasi Decision Tree

Advance development of social media application has affected to human lifestyle. Everyone can obtain information from social media easyly. Its become easier to communicate each other using social media. Twitter is one of the fastest growing social media application. Deliver good and hoax information from one user to another. Event there are alot of fake account (bot) in Twitter. This objection of this study is to detect Twitter Bot accounts on Twitter social media by using the Decission Tree classification. Experiment results show the accuracy performance of the Decision Tree model reached 88.84% and UC curve by 0.965. Its shows that the Decision Tree classification is excellent in detecting Twitter Bot accounts.
Strategi Dalam Meningkatkan Kompetensi dan Profesionalisme Pustakawan dalam Mengoptimalkan Kembali Reference Service terhadap Pemustaka di Perpustakaan Universitas Negeri Padang

ABSTRACT&#x0D; The reference service at the library is currently less than optimal. Therefore, several strategies are needed to improve the competence and professionalism of librarians in reference services. One of the reference services that still needs optimization in improving the competence of librarians is the Padang State University Library. The method used in this article is a qualitative method with a descriptive approach. This type of research in writing this article uses the Research Library method which means a literature or literature study. The purpose of this research is to find out the strategies used by libraries to improve the competence and professionalism of librarians in reference services and to find out what the obstacles are in the Padang State University Library.&#x0D;
Implementing Azure Networking

Azure has multiple methods in which administrators can connect to their on-premises environment and extend their datacenter into the cloud. Different workloads, security considerations, and routing requirements of the various use cases may warrant a combination of a few different types of connections.
Classes – Inheritance and Polymorphism

In this chapter, we discuss some of the fundamental building blocks of object-oriented programming, such as inheritance and polymorphism.
Study on track planning problem of multi-constrained and double-targeted

Aiming at the positioning error of the aircraft, the error accumulation to a certain extent may lead to the failure of the mission. A track correction method based on oriented graph search was proposed, and the dynamic programming idea was applied to solve the path optimization problem. Firstly, the correction points in the flight space were preprocessed, and the planning of the correction points in the flight space was transformed into a graph theory problem. It effectively solves the problem that traditional methods did not adapt well to dynamic changes in flight space. And the problem of too high complexity in the calculation space. Using the dynamic programming idea to carry out the flight path planning for the flight space, the path-correction number optimal double-objective model is comprehensively established. Finally, the oriented graph and dynamic programming ideas were used to solve the problem, and the visual analysis of the aircraft track was realized. The simulation results show that the established path-corrected optimal double-objective model can calculate an optimal track with relatively small correction times and short length.
Characterizing an Analogical Concept Memory for Architectures Implementing the Common Model of Cognition

Architectures that implement the Common Model of Cognition - Soar, ACT-R, and Sigma - have a prominent place in research on cognitive modeling as well as on designing complex intelligent agents. In this paper, we explore how computational models of analogical processing can be brought into these architectures to enable concept acquisition from examples obtained interactively. We propose a new analogical concept memory for Soar that augments its current system of declarative long-term memories. We frame the problem of concept learning as embedded within the larger context of interactive task learning (ITL) and embodied language processing (ELP). We demonstrate that the analogical learning methods implemented in the proposed memory can quickly learn a diverse types of novel concepts that are useful not only in recognition of a concept in the environment but also in action selection. Our approach has been instantiated in an implemented cognitive system \textsc{Aileen} and evaluated on a simulated robotic domain.
Self-Regulated Learning Bagi Mahasiswa: Pentingkah?

An indicator of learning process run well can be measured through student’ academic achievement. Self-regulated learning is assumed has a connection with student academic achievement. It is known that every students has self regulatory to control their learning activities. The research used quantitative approach and to examine the effect of student’ self-regulated learning skills on academic achievement. This study involved 162 students. The results showed that self-regulated learning skills influence academic achievement. The higher self-regulated learning skill, the higher academic achievement is achieved. This result useful for further research to develop learning process that provide opportunity to enhance students self-regulated learning skills. DOI: https:// dx.doi.org/10.17977/ um014v13i12020p069
The Safety Management of University Campus Network

The development of the Internet in higher education, teaching, scientific research, management and service plays an increasingly important role, but the safety management of university campus network problems also increasingly protruding comes out now. Therefore, we must strengthen the campus network security management consciousness, improve the campus network security management system, create a campus network security work environment, to ensure the safe operation of campus network.
Enabling Premium Service for Streaming Video in Cellular Networks

Streaming video applications require high bandwidth for desired quality of experience (QoE), and they are driving rapid growth of mobile data traffic in cellular networks. Currently, cellular networks provide best-effort services to most user data applications. When there is congestion at the base station, streaming video applications will experience degraded QoE. In this paper, we take a cellular service provider’s perspective and propose a premium service for improving QoE of streaming video applications. We design and implement a network adaptation scheme called SHADE, which allocates limited transmission resources at the base station among applications smartly, by (i) selecting a candidate bitrate for each streaming video application, and (ii) maintaining the downlink throughput at this targeted bitrate for better QoE, while still using the Non-Guaranteed Bit Rate traffic class which is suitable for high bit-rate streaming video. We demonstrate that SHADE can achieve this with high network utilization and improve QoE for streaming video applications, and with bounded negative performance impact to other applications. Our extensive experiments show that SHADE can significantly improve three key streaming video application QoE metrics simultaneously (up to 10 times improvement), compared to current practice. We discuss how cellular carriers and equipment vendors can adopt SHADE without major changes to current cellular network implementation.
DESIGN A LOW COMPLEX VLSI ARCHITECTURE OF IDENTITY BASED FULLY HOMOMORPHICENCRYPTION & DECRYPTION (IBFHED)

ABSTRACT: In this paper, design of the Low Complex VLSI Architecture of Identity Based FullyHomomorphic Encryption and decryption (IBFHE). This system will provide better security and resourceefficiency compared to existing standards. Identity based fully homomorphic encryption and decryptiontechnique guarantee both privacy and integrity. The main intent is to increase the speed of operation. Firstly, bitsare subtitled using S-Box. After substitution of bytes, the bits will be matched based on the matching procedure.After matching shifting operation is performed. Bits will be shifted in row manner and mixed in column wiseusing mix column technique. Now these bits are encrypted. At last inverse operation is performed to get exactoutput. In existed system encryption process is performed (i.e) plain text is converted into cipher text. Because ofthis there will be no proper security. Hence identity based fully homomorphic encryption and decryption isimplemented (i.e) plain text is converted into cipher text & cipher text is converted into plain text. Hence thisproject gives better security compared to exist one.
A Biological Perspective to Leadership and Team Processes

Although leadership and team processes are among the most studied topics in management, there is a growing concern over both theoretical and methodological aspects of their conceptualization and measurement. In this symposium, we highlight the potential of biological and neuroscience techniques to begin to address these limitations by extending theory and offering new methodologies. For instance, the presenters will offer research that extends work on leadership and team emergent/contagion processes by focusing on neurological and physiological synchrony. Another goal of this symposium would be to demonstrate the feasibility of utilizing biological/neuroscience tools in the study of other areas of management beyond leadership and team processes. Each of the presentations in this symposium will focus on different constructs and biological methodologies. Beginning with Danni Wang and colleagues who will highlight the assessment of team emergent processes using quantitative electroencephalogram (qEEG); Nir Milstein, Ilanit Gordon, and Steve Blader who will demonstrate the role of physiological synchrony in explaining the effects of interactional justice on team outcomes; Yair Berson and Avi Goldstein will present experimental findings from magnetoencephalography (MEG) scanner revealing the effects of visionary leadership on neurological synchrony; Joel Andrus and David Sullivan will approach gender biases in entrepreneurship via EEG and galvanic skin response (GSR) techniques; and Sean Hannah, who will report on research conducted to assess ethical leadership through EEG. Finally, Neal Ashkanasy will discuss these presentations emphasizing both advantages and disadvantages of these research practices and their utilization in our field. Capturing Team Dynamics with Neuroscience Presenter: Danni Wang; Rutgers Business School Presenter: Pierre Balthazard; California State U. Sacramento Presenter: Maja Maja; Microsoft Presenter: Nicola M. Pless; ESADE Presenter: Thomas Maak; U. of Melbourne Presenter: Chris Berka; Advanced Brain Monitoring Presenter: Travis Richardson; Arizona State U. The Role of Physiological/Behavioral Synchrony in Mediating the Effects of Justice on Group Outcomes Presenter: Nir Milstein; Bar-Ilan U. Presenter: Steven Blader; New York U. Presenter: Ilanit Gordon; Bar Ilan U. The Effects of Visionary Leadership on Followers’ Neurological Presenter: Yair Berson; Bar-Ilan U. and NYU-Stern Presenter: Abraham Goldstein; Bar Ilan U. Making the Glass Ceiling: Unconscious Gender Biases on Entrepreneurial Funding Decisions Presenter: Joel Andrus; U. of Missouri Presenter: David Walter Sullivan; Texas A&M U. Lesson-Learned from a Neuroscience Journey Presenter: Sean Hannah; Wake Forest U.
Sprites for Solo Clarinet

Author(s): Middleton, Andrew | Abstract: This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.
An Assessment of Language Identification Methods on Tweets and Wikipedia Articles

Language identification is the task of determining the language which a given text is written. This task is important for Natural Language Processing and Information Retrieval activities. Two popular approaches for language identification are the N-grams and stopwords models. In this paper, these two models were tested on different types of documents such as short, irregular texts (tweets) and long, regular texts (Wikipedia articles).
Perbandingan Algoritma Elias Delta Code dengan Levenstein Untuk Kompresi File Teks

A text file is a collection of characters or strings that become a single unit. Text that contains many characters in it always causes problems in the storage media and the speed of time when transmitting data. Text file is a file that contains information in the form of text. Data derived from word processing documents, numbers used in calculations, names and addresses in the database are examples of text data input consisting of characters, numbers and punctuation marks. Seeing the need for data compression it is necessary to compress or compress data that can reduce data, thus gaining the advantage of reducing the use of external storage media space, accelerating the process of transferring data between storage media, compressing data with a higher ratio than the original data. The compression process is done by comparing several algorithms to overcome problems in storage media, where the method for compression using the Elias Delta Code Algorithm and the Levenstein Algorithm.
Fully symbolic-based technique for solving complex state-space control systems

Despite the superiority of symbolic approaches over the purely numerical approaches in many aspects, it does not receive the proper attention due to its significant complexity, high resources requirement and long drawn time which even grows significantly with the increase of model dimensions. However, its merits deserve every attempt to overcome the difficulties being faced. In this paper, a fully generic symbolic-based technique is proposed to deal with complex state space control problems. In this technique, depending on the model dimension if exceeds a predefined limit, the state space is solved using the partitioned matrices theory and block wise inversion formula. Experimental results demonstrate that the proposed technique overcomes all the previously mentioned barriers and gives the same results when compared to numerical methods (Simulink). Moreover, it can be used to gain useful information about the system itself, provides an indication of which parameters are more important and reveals the sensitivity of system model to single parameter variations.
Foreign Investors and Governance Quality in Extreme Institutional Environments

We draw on practice transfer theory to advance the corporate governance mobility literature by developing a framework that uncovers how foreign institutional investors (FIIs) transfer and improve on corporate governance practices of firms in challenging institutional environments. Using hand-collected data for 85 listed Nigerian firms covering 2011-2016 period, we show that FIIs bypass information disadvantage, weak governance enforcement institutions in extreme institutional environments by transferring good governance standards to firms in the host country of investment. More so, we show that the severity of FIIs transfer and enhancement of corporate governance quality of firms in challenging institutional environments is positively moderated by their legal origin. Specifically, FIIs from common law countries significantly enhance the ability of these investors to transfer and improve on the CG practices of firms in challenging emerging economies. On the other hand, high cultural distance between FIIs country of origin and the investment country negatively moderate this relationship. Our results are robust to the choice of estimation method, sample selection, and control for other factors that influence corporate governance practices. We also highlight theoretical and practical implications of the study.
Direct 3D Organ Extraction Method in Virtual Human-Body Color Volume Image

Extracting 3D structures from voxel based images can make doctors more directly observe the situation of the target in the clinic, making it easier for doctors to diagnose the condition and make the medicine teaching more directly and easier to understand. For this purpose, we propose a 3D volume image segmentation method based on the max-flow/min-cut algorithm. Our segmentation method can be applied directly to 3D volume image. After users marking small amount tags (foreground and background pixels), we put forward a method to use a directed connected graph structure to represent the volume image. In the directed connected graph, in order to speed up the efficiency of the segmentation in subsequent steps, we divide each voxel node in the graph into different color ranges, and each color range match up with an auxiliary node. In order to divide the color range more finely, we propose a method to calculate the color similarity. We then use the max-flow/min-cut algorithm to segment the directed connected graph. The result of experiments performed in multiple sets of slice images shows that our proposed method improves the efficiency, reduces human error on the 3D volume image segmentation task, and the result is complete and accurate.
Presentations from the 2019 SHRM Foundation Dissertation Award Winners

Academy of Management Annual Meeting Proceedings includes abstracts of all papers and symposia presented at the annual conference, plus 6-page abridged versions of the “Best Papers” accepted for inclusion in the program (approximately 10%). Papers published in the Proceedings are abridged because presenting papers at their full length could preclude subsequent journal publication. Please contact the author(s) directly for the full papers. Presentations from the 2019 SHRM Foundation Dissertation Award WinnersEric J. Michel, Nitya Chawla, Xing Liu, Shoshana Schwartz and Yu YuEric J. MichelNorthern Illinois U. , Nitya ChawlaTexas A&M U. , Xing LiuU. of South Carolina , Shoshana SchwartzThe Wharton School, U. of Pennsylvania" and Yu YuSchool of Economics and Management Tsinghua U. Published Online:29 Jul 2020https://doi.org/10.5465/AMBPP.2020.10099symposiumAboutSections ToolsDownload CitationsAdd to favoritesTrack Citations ShareShare onFacebookTwitterLinkedInRedditEmail AbstractThis symposium is composed of four 2019 SHRM Foundation Dissertation Award winners’ presentations based on their dissertations: ""Does Leadership at Different Organizational Levels Matter in Human Resource Management? The Role of Leader Proactive Personality"" presented by Yu Yu, ""Team Creativity after Having New Hires: The Influence of Established Social Structures among Incumbents and Information Elaboration between Incumbents and New Hires"" presented by Xing Liu, ""Gender Disparities in the Prices that Employers Charge for Their Employees’ Services"" presented by Shoshana Schwartz, and ""From Crude Jokes to Diminutive Terms: Exploring Experiences of Hostile and Benevolent Sexism During Job Search"" presented by Nitya Chawla.FiguresReferencesRelatedDetails Vol. 2020, No. 1 Permissions Metrics Downloaded 0 times in the past 12 months History Published online 29 July 2020 Published in print 1 August 2020 InformationCopyright of Academy of Management Journal is the property of Academy of Management and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder’s express written permission. However, users may print, download, or email articles for individual use.KeywordsAOM Annual Meeting Proceedings 2020
Lessons for ERP Implementation Vendor Selection in National Grid USA Service Company, Inc. v Wipro Ltd. — A case study from yet another failed SAP ERP Implementation Project

Article Lessons for ERP Implementation Vendor Selection in National Grid USA Service Company, Inc. v Wipro Ltd. — A case study from yet another failed SAP ERP Implementation Project was published on April 1, 2020 in the journal Computer Law Review International (volume 21, issue 2).
The Role of CSR in the Relationship Between Social Trust and Financial Performance

Institutional theorists suggest country-level informal institutions influence the economic prosperity of countries and firms. In this study, we examine the relationship between country-level social trust and firm-level financial performance, emphasizing the role of corporate social responsibility (CSR) as a mediator. In a society with strong social trust, individuals and organizations are expected to cooperate and behave honestly. Accordingly, individual interactions are guided by the norms of trustworthiness and the willingness to trust others. This study proposes that a firm can satisfy the norm of social trust by committing to socially responsible activities, which, in return, positively influence a firm’s financial performance. Our analysis based on various data sources partially supports our theory. Although the mediation effect of CSR is found to be significant when a firm’s financial performance is measured by return on assets (ROA), it is not significant when return on equity (ROE) is used as a financial performance proxy.