Reviewerly/exHarmony huggingface dataset:
Penerapan Metode Web Engineering pada Sistem Informasi Ruang Terbuka Hijau Dinas Pekerjaan Umum dan Penataan Ruang Kota Pagar Alam

This study aims to produce a Green Open Space (RTH) information system of the Pagar Alam City Public Works and Spatial Planning (PUPR) using the Web Engineering method. Based on observations at PUPR Office Pagar Alam City, it is found that the delivery of information that is currently running is still manual by using brochures, pamphlets, banners, inefficient counseling, and not many people can receive information. Causing many domestic and foreign tourists who do not know the places of Green City Pagar Alam. This research uses the method of developing a Web Engineering system with the following steps: Costumers Communication, Planning, Modeling, Construction and Depeloyment. As well as using Google Maps as a search place. Based on the results of testing that the functionality of the information system can be run well without any obstacles from the process, testing is done using the Black Box method. With this information system, it useful to provide users with easy information about Green Pagar Alam City.
A Named Entity Based Approach to Model Recipes

Traditional cooking recipes follow a structure which can be modelled very well if the rules and semantics of the different sections of the recipe text are analyzed and represented accurately. We propose a structure that can accurately represent the recipe as well as a pipeline to infer the best representation of the recipe in this uniform structure. The Ingredients section in a recipe typically lists down the ingredients required and corresponding attributes such as quantity, temperature, and processing state. This can be modelled by defining these attributes and their values. The physical entities which make up a recipe can be broadly classified into utensils, ingredients and their combinations that are related by cooking techniques. The instruction section lists down a series of events in which a cooking technique or process is applied upon these utensils and ingredients. We model these relationships in the form of tuples. Thus, using a combination of these methods we model cooking recipe in the dataset RecipeDB to show the efficacy of our method. This mined information model can have several applications which include translating recipes between languages, determining similarity between recipes, generation of novel recipes and estimation of the nutritional profile of recipes. For the purpose of recognition of ingredient attributes, we train the Named Entity Relationship (NER) models and analyze the inferences with the help of K-Means clustering. Our model presented with an F1 score of 0.95 across all datasets. We use a similar NER tagging model for labelling cooking techniques (F1 score = 0.88) and utensils (F1 score = 0.90) within the instructions section. Finally, we determine the temporal sequence of relationships between ingredients, utensils and cooking techniques for modeling the instruction steps.
Controlling contrast and luma of digital images by transformation of pixel brightness through power function

The article considers the possibility of controlling the brightness and contrast of the digital image by transformation of the pixel brightness through the power function. Analysis of the parameters of the converted images on the simple model of dark low contrast image has been carried out. The preferred values of parameters and possible ranges of brightness and contrast are determined. The results of transformation of the dark low contrast images compared with the results of image processing by other methods (approximated by reduction of a histogram to a uniform distribution and a television algorithm) are investigated. It has been stated that the parameters of the considered transformation can be chosen, so that the improvement of the distinguishability of the image details will be much better than using the methods with which the comparison is made.
Countering the Unverified Health Related Information

The article is intended to offer the strategy to tackle the wrong and unverified information related to health issues.It is based on the data of a survey in East Java, the province with the second largest population in Indonesia, and the second largest economic in the country.The data shows that people in East Java admitted that they were expose to many incorrect and unverified health information, through various channels, such as personal chatting applications, mainstream/conventional media, and social media.The survey revealed that people responded differently to unverified health information.Some found clarity, but others felt anxious.The fact that people think they can get clarity though the information from social media and the Internet, are not sufficiently verified is upsetting.Trusting untested or clinically unproven health information can be harmful and dangerous.A way to counter the propagation of untested health information or unverified information sources is to use the same information channels to distribute the guidance to inform people how to identify the wrong and untested health information.And, by the same measure it could also empowering people to fight against such false information.
EMPLOYEE SELF SERVICE (ESS) ONLINE IN PT. DATA UTAMA

PT. Data Utama is a company that organizes professional - international trade shows that have500 permanent employees, 50 contract employees and 10 daily employees. PT. Data Utama hasmany divisions / department, one of which is the Human Resources Department (HRD) whichhas many documents for all employees. One of the duties of HRD is to manage the employee'sApplication for Permit (SPI). During this time in managing SPI, the HR department stillcollected SPI forms from employees. In the process of applying for permits and taking leave ofleave, the manual process still uses the application letter submitted to the supervisor. Then theSPI that has been approved by the employer, therefore needs to submit an SPI form to the adminsection of the HRD for ratification of the employee permit application. This causes the work ofemployees &amp; HRD to be ineffective and inefficient. For this problem, an online Employee SelfService (ESS) information system was created. The study was conducted using surveytechniques, where primary data collection was taken by distributing questionnaires to severalparts of PT. Data Utama. The expected results are knowing that this application can facilitatethe management of employee permit applications, so that from the input process to the searchfor data that becomes easier, faster and more efficient.
The problem of quality management in higher education: contrasting views of the teacher and the university

Planning and Teaching Engineering Staff for the Industrial and Economic Complex of the Region 2019: Proceedings of 2019 XVIII Russian Scientific and Practical Conference on Planning and Teaching Engineering Staff for the Industrial and Economic Complex of the Region (PTES)
Revisiting Initialization of Neural Networks

The proper initialization of weights is crucial for the effective training and fast convergence of deep neural networks (DNNs). Prior work in this area has mostly focused on balancing the variance among weights per layer to maintain stability of (i) the input data propagated forwards through the network and (ii) the loss gradients propagated backwards, respectively. This prevalent heuristic is however agnostic of dependencies among gradients across the various layers and captures only firstorder effects. In this paper, we propose and discuss an initialization principle that is based on a rigorous estimation of the global curvature of weights across layers by approximating and controlling the norm of their Hessian matrix. The proposed approach is more systematic and recovers previous results for DNN activations such as smooth functions, dropouts, and ReLU. Our experiments on Word2Vec and the MNIST/CIFAR image classification tasks confirm that tracking the Hessian norm is a useful diagnostic tool which helps to more rigorously initialize weights
SECURE CRYPTOGRAPHY KEY MANAGEMENT SYSTEM FOR WEB BASED WALLET MANAGEMENT SYSTEM

Cryptocurrencies are getting massive momentum in the last few years.Cryptocurrencies depend upon a secure distributed ledger called blockchain which stores blocks in a secure and chronological order.Although a large cryptocurrencies wallet management scheme has been proposed but they suffer from weak security.Thus effective cryptocurrency key management has become a much needed requirement for modern cryptocurrencies.In this paper, we propose a more effective, usable and secure cryptocurrency key management system named rashi that provides security enhanced storage, no password authentication.The performance analysis shows that our proposed system requires minimal additional overhead and has low time delays, enhanced security and efficient real -world deployment.
LibGuides: Library Course Reserves: Starting Lists in Leganto

Library Course Reserves use Leganto. Created by Ex Libris, Leganto is an online application that supports the creation and management of course resource reading lists.
Multicore processors and GPUs: the power of parallel computing in the Cloud

Sensors used in intelligence, surveillance and reconnaissance (ISR) operations and activities have the ability to generate vast amounts of data. High-volume analytical capabilities are needed to process data from multi-modal sensors to develop and test complex computational and deep learning models in support of the U.S. Army Multi-Domain Operations (MDO). The Army Research Laboratory designs, develops and tests Artificial Intelligence and Machine Learning (AI/ML) algorithms employing large repositories of in-house data. To efficiently process the data as well as design, build, train and deploy models, parallel and distributed algorithms are needed. Deep learning frameworks provide language-specific, container-based building blocks associated with deep learning neural networks applied to specific target applications. This paper discusses applications of AI/ML <i>deep</i> learning frameworks and Software Development Kits (SDKs) and demonstrates and compares specific multi-core processor and NVidia Graphics Processing Unit (GPU) implementations for desktop and Cloud environments. Frameworks selected for this research include PyTorch and Matlab. Amazon Web Services (AWS) SageMaker was used to launch Machine Learning instances ranging from general purpose computing to GPU instances. Detailed processes, example code, performance enhancements, best practices and lessons learned are included for publicly available acoustic and image datasets. Research results indicate parallel implementations of data preprocessing steps saved significant time but more expensive GPUs did not provide any processing time advantages for the machine learning algorithms tested.
Flexible framework for audio restoration

The paper presents a unified, flexible framework for the tasks of audio inpainting, declipping, and dequantization. The concept is further extended to cover analogous degradation models in a transformed domain, e.g. quantization of the time-frequency coefficients. The problem of restoring an audio signal from degraded observations in two different domains is formulated as an inverse problem, and several algorithmic solutions are developed. The viability of the presented concept is demonstrated on an example where audio restoration from partial and quantized observations of both the time-domain signal and its time-frequency coefficients is carried on.
Development of Personality, Cognitive Skills and Creative Abilities of Preschoolers Through the Implementation of Family Projects

The experience of organizing project activities aimed at supporting and developing the intellectual and creative potential of over-fives, as well as family values, interests and involving parents in joint activities with children is presented in the article. This work is designed for educators and teachers working with preschoolers.
Ship Detection in Remote Sensing Optical Imagery using Machine Learning

The requirements for nations to patrol and protect their maritime borders and international waters is vital to securing economic assets, preventing illegal immigration and monitoring other countries military and commercial behavior. The large increase of military and government surveillance satellites has led to an influx of remote sensing datafor which human analysis is time consuming. A recent rise of machine learning techniques such as convolutional neural networks (CNN) has allowed humans to hand over complex tasks like object detection to computer algorithms. This report aimed to conduct optimisation of a hand-built CNN as well as fine-tuning existing state of the art CNNarchitectures in the task of ship classification in optical remote sensing data. This report was able to achieve a maximum accuracy of 94.8% on a fine-tuned Xception model with no optimisation, outperforming a carefully optimised handmade network by approximately 5%. It was concluded that for this complex classification task an existing state-of-the-art model should be fine tuned to achieve the highest accuracy.
Universal Transformations of Managed Strategies for Transition to the Status of a Transitional University

The world is changing rapidly. New realities become the subject of conceptualization, established theoretical concepts give way to new emerging constructs. In particular, the authors have previously refined the concepts of "transit university" and "transitive university". In the context of global, national and regional challenges for the transition of a regional transit university to the status of a transitive university, the position of the university leadership on creating an innovative university ecosystem as a driver for the development of the region becomes fundamentally significant. Accordingly, the purpose of the study was to clarify the resources and direction of changes in the internal university management of a regional university, necessary to ensure its transitivity. Universal transformations of managerial strategies for transition to the status of a transitive university are considered through the prism of modern global, national and regional challenges. The article analyzes the need for diversification of educational national and regional systems against the background of universalization of requirements for higher education institutions of international rating agencies. In particular, attention is drawn to the fact that in the transition to the status of a transitive university, the diversification strategy also receives an internal component, represented by the need to find a balance between traditional academic values and the values of market competition; between global and local awareness of opportunities for attracting students and teachers; between preferences in providing hard- and soft skills. It also substantiates the importance of developing strategies for the constancy of transformation and the formation of a strong managerial core. The persistence of the interface between adaptive and proactive changes in the internal and foreign policies of the university administration is seen as an everyday strategic task that does not have unambiguous tactical decisions and is complicated by the existing gaps in the competencies of the heads of Russian and foreign universities. We consider the resources of transformational changes associated with the need for comprehensive digitalization of the university, with the development of a digital format of work in administration, the organization of educational and research processes as a new reality of university management, with the transition to working with big data; and also – formats for collegial interaction in creating innovative university ecosystems.
Research Guides: Using HathiTrust: Searching in HathiTrust

Description of how to find and use Hathi Trust resources at the University of New Hampshire
The Integration of SAP Software in Learning Accounting Information Systems to Face Industrial Revolution 4.0

&lt;p class="JurnalASSETSABSTRAK"&gt;ABSTRACT&lt;/p&gt;&lt;p&gt;This study aims to improve student competence by integrating SAP in the SIA course in the industrial revolution 4.0. This research is a classroom action research. Data analysis methods used are quantitative and qualitative. Qualitative analysis is done by identifying the weaknesses and strengths of the application of actions and analyzing critical points. Quantitative analysis was performed by paired sample t-test to strengthen the results of the study. The results showed that there was an increase in student competence from moderate to high in cycle 1. This result was also supported by the results of paired sample t-tests which showed that there was a difference in student competence before and after the integration of SAP in SIA courses.&lt;/p&gt;&lt;p class="JurnalASSETSABSTRAK"&gt;&lt;em&gt;ABSTRAK&lt;/em&gt;&lt;em&gt;&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;Penelitian ini bertujuan untuk meningkatkan kompetensi mahasiswa dengan mengintegrasikan SAP dalam MK SIA dalam menghadapi revolusi industri 4.0. Penelitian ini merupakan penelitian tindakan kelas. Metode analisis data yang digunakan adalah kuantitatif dan kualitatif. Analisis kualitatif dilakukan dengan mengidentifikasi kelemahan dan kelebihan penerapan tindakan serta menganalisis titik kritis. Analisis kuantitatif dilakukan dengan paired sample t-test untuk memperkuat hasil penelitian. Hasil penelitian menjukkan bahwa terdapat peningkatan kompetensi mahasiswa dari sedang ke tinggi pada siklus 1. Hasil ini juga didukung oleh hasil paired sample t-test yang menunjukan terdapat perbedaan kompetensi mahasiswa sebelum dan sesudah tindakan yaitu diintegrasikannya SAP dalam mata kuliah SIA.&lt;/em&gt;&lt;/p&gt;
Selection of Connecting Phrases in Weather Forecast

In this paper, we present an approach to select the most appropriate phrases in a weather forecast, when the numerical weather data is present. We study the different types of connecting phrases present in weather forecast and the challenges involved in selecting them. We use a classification-based approach for selecting the connecting phrases in the weather forecast. We evaluate our results on a standard weather forecast dataset and compare our results with a similar previous work. Our approach outperforms the previous work and provides a new state-of-the-art results.
BROWSER-BASED COMPUTER BUSINESS GAME AS AN INTERACTIVE LEARNING ENVIRONMENT FOR MANAGERS

The article addresses the issue of quality improvement for students’ training under the “Management” specialization using the latest type of computer business games – the browser-based game “Practical Marketing”.The experience of using this game in the educational process is summed up. The didactic features of the game as an interactive learning environment that is modeling economic reality are reviewed. The analysis of the game play and the algorithm for developing an effective game strategy has been carried out. A game sheet for game participants has been developed.Recommendations have been prepared for teachers on the use of the game in various disciplines to increase the effectiveness of students’ training under the “Management” specialization and to develop their strategic thinking skills.
Using the Latin Square Design Model in the Prioritzation of Network Security Threats: A Quantitative Study

Society is becoming increasingly dependent on cyberspace for both business and pleasure.Cyber attackers continue to attack organizational computer networks, as those same computer networks become increasing critical to organizational business process.Strategic planning and managing IT security risks play an important role in the business and government planning process.Deploying defense in depth security measures can ensure that organizations continue to function in times of crisis.This quantitative study explores whether the Latin Square Design (LSD) model can be effectively applied to the prioritization of cybersecurity threats and to the linking of information assurance defense in-depth measures to those threats.The methods used in this study consisted of scanning 10 Cybersecurity Websites such as the Department of Homeland Security US CERT (United States-Computer Emergency Readiness Team [1]) and the SANS Institute (SysAdmin, Audit, Network and Security [2]) using the Likert Scale Model for the Website's top ten list of cyber threats facing organizations and the network defense in depth measures to fight those threats.A comparison of each cybersecurity threats was then made using LSD to determine whether the Likert scale and the LSD model could be effectively applied to prioritize information assurance measures to protect organizational computing devices.The findings of the research reject the H 0 null hypothesis that LSD does not affect the relationship between the ranking of 10 Cybersecurity websites top ten cybersecurity threats dependent variables and the independent variables of defense in depth measures used in protecting organizational devices against cyber-attacks.
Security of Gestures Based CAPTCHAs

We present a security analysis of several gesture CAPTCHA challenges designed to operate on mobiles. Mobile gesture CAPTCHA challenges utilize the accelerometer and the gyroscope inputs from a mobile to allow a human to solve a simple test by physically manipulating the device. We have evaluated the security of gesture CAPTCHA in mobile devices and found them resistant to a range of common automated attacks. Our study has shown that using an accelerometer and the gyroscope readings as an input to solve the CAPTCHA is difficult for malware, but easy for a real user. Gesture CAPTCHA is effective in differentiating between humans and machines.
Development of Design for Enhancing Trust in Cloud’s SPI Stack

Cloud computing defines the SPI model, which is generally agreed upon as providing Software-as-a-Service, Platform-as-a-Service and Infrastructure-as-a-Service. Interest in those service delivery models is growing because the paradigm offers to cloud customers high computational resource on-demand with a low cost. However, trustiness in the cloud services regarding the security and the privacy of the delivered data is the most critical issue in the SPI model. In this paper we propose a trusted SPI model that gives cloud customer more confidence into SPI services by leveraging a trust in a neutral SPI certifying authority. The proposed model prevents insider attacks from tampering with application service before and after the computational resource was launched and allow cloud customer to verify if its node run in a secure environment
Subject & Course Guides: Optical Character Recognition (OCR) - Getting Started: OCR Projects

Basic overview of several tools (both open source such as Tesseract and commercial such as Adobe Acrobat) that perform optical character recognition (OCR).
Best practices for password hashing and storage

This document outlines best practices for handling user passwords andother authenticator secrets in client-server systems making use ofSASL.
Tasks of Situational Analysis in Psychology of Management

This article is an invitation to a discussion about the meaning and content of management in the modern world and the search for a new management paradigm in the 21st century. The challenge to modern management comes from the nature of the forces, changes and processes taking place in the world. The tasks of situational analysis are proposed as effective ways to determine the factors affecting the development of the organization and the place occupied by the organization in the general economic space.