Reviewerly/exHarmony huggingface dataset:
Resúmenes al Español

Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation Resúmenes al Español. Am J Intellect Dev Disabil 1 November 2020; 125 (6): 513–515. doi: https://doi.org/10.1352/1944-7558-125.6.513 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest Search
Data Hiding in Grayscale Image using Least Significant Bit Technique and Discrete Wavelet Transform

In this paper, we present a model for data hiding using modified least Significant Bit and DWT concept to further improve the ability to embed as a picture good (EC).From the begin, each high-quality pixel produces 4 new pixels. The puzzle facts is concealed in all the four conveyed pixels. via then the pixels are fixed to improve the concept of the stego-pics. There are four separate stego-pictures crafted from the four unmistakable revised pixels. each stego-photo disguises one piece for every pixel. For Stego-photos, the typical peak signal-to-noise ratios (PSNR) the proposed procedure successfully withstand against RS-stego examination
An Extended Hybrid Clustering Method Utilzing Svm as Cross Validator

The massive data accumulation from the internet creates attention for the researchers. The data collected in the form of structured and unstructured data. The structured data consists of messages, transactions, conversations, etc. while unstructured represents video and audio clips. This essentially manages the raw data problem in which unreferenced clustering is used. A hybrid approach is proposed using Cosine Similarity and soft cosine. A novel clustering technique is designed which is cross-validated using the Support Vector Machine (SVM). The validated approach is further verified by using K- means clustering. The clustering results have been further evaluated using parameters precision, recall, and F-measure. The evaluated results show the improvement in precision and recall accuracy due to hybridization of cosine similarity and soft cosine techniques.
The Community Cybersecurity Maturity Model (CCSMM)

Lessons learned from the community cyber security exercises showed common threads each community needed to focus on in order to improve the community's cyber security posture. These similarities were grouped into four areas of improvement called dimensions. The dimensions are awareness, information sharing, policies, and planning. The methods in which communities can implement improvement are called implementation mechanisms. These mechanisms are common approaches used every day such as establishing metrics, implementing technologies, creating processes and procedures, and conducting training and assessments.
PENERAPAN KONSEP E-LEARNING DENGAN METODE GAMIFIKASI UNTUK MENINGKATKAN KUALITAS PEMBELAJARAN DI PERGURUAN TINGGI

To meet the needs of digital transformation, Indonesia needs young people who are able to compete globally. The education industry has taken advantage of this trend by integrating new methods such as virtual collaboration, mobile learning applications and enhanced learning technologies. In this study, researchers tried to apply the concept of Elearning / distance learning using the gamification method so as to improve the quality of learning in higher education. Gamification method provides additional motivation to ensure students (learners) follow complete learning activities and the ability to solve problems.
Мобильное библиотечное обслуживание на примере Новосибирской областной детской библиотеки им. А. М. Горького

In the article, the author describes in detail the process of providing mobile services to readers. An effective method of service - bibliobus service - has been introduced by the library by delivering the necessary literature for the needs of the population living in remote areas. Another advantage of the mobile library is that it is available as a mobile library in places where people gather and hold cultural events. In order to promote and expand the resources of the library, the project "Book in Action" was launched in collaboration with the Novosibirsk regional railways, and today it is recognized as one of the most effective methods of service. There is a special carriage on the train, equipped with the necessary technological equipment and furniture. At present, it serves the passengers to have a good time and is of great interest to passengers.
What Do We Now Know About the Creative use of Figurative Communication in Advertising?

Chapter 11 shows how figurative messaging can be used in the most optimal way in advertising campaigns and branding exercises. It provides recommendations designed to help practitioners to make informed choices about the use of figurative messaging in their campaigns and to anticipate possible outcomes and pitfalls. It covers issues such as the way in which metaphor works as a ‘disruptor’, how people experience and interact with metaphor, the different ways in which figurative messaging can be used creatively, how this relates to fast and slow thinking, and the ways in which figurative messaging can be made to appeal to different audiences.
Circular Archetypes

We live in a ‘throwaway and replace’ culture. Our growing population and demand for new products has placed huge pressures on our planet’s resources. The research argues design can play a strategic role in supporting the adoption of new mindsets, methods and models to enhance awareness and understanding of the need to design for a circular economy. This paper provides a practical example. Drawing upon a feasibility study into Makerspaces, it will explore how they might be developed in the future to support circular innovation, within the context of textiles, to address complex issues around material waste. The insights drawn from this research act as a starting point for future work, reflecting on the implications of the methods applied, concluding the circular economy is the same imperative whether people are focusing on ecology, economy or just their own business. Furthermore, it will suggest that design-led approaches play a role in embedding collaborative ways of working to integrate sustainability into the business modelling process.
Create Marketing Strategies for Maximum Impact

Special Events GaloreVolume 20, Issue 5 p. 5-5 Milestone Anniversary Planning Create Marketing Strategies for Maximum Impact First published: 09 April 2020 https://doi.org/10.1002/speg.31348Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume20, Issue5May 2020Pages 5-5 RelatedInformation
Capacity Preserve Assignment Scheduling Algorithm in context of Determination System for Cloud Computing

Booking figuring is reliably a fervently issue in appropriated processing condition. Remembering the true objective to take out system bottleneck and modify stack logically. A stack changing endeavor booking count in light of weighted self-assertive and input frameworks was proposed in this paperFrom the outset the picked cloud masterminding host picked assets by necessities and made static estimation, and some time later coordinated them; other than the tally picked assets from which composed by weight self-confidently; by then it got standing out powerful data from effect burden to channel and sort the left. Finally it accomplished oneself adaptively to structure stack through information systems. The examination demonstrates that the calculation has stayed away from the framework bottleneck adequately and has accomplished adjusted burden and furthermore self-flexibility to it.keywords: Task Scheduling; Feedback Mechanism; Cloud Computing; Load Balancing
Role of Information and Communication Technology in Economic Development of India

Information and Communication Technology (ICT) stresses the role of unified communication and integration of telecommunications, intelligent building management systems and audio-visual systems in modern information technology. In the information age, using information is a prime issue. ICT includes of all technical means that are used to handle information and aid communication. It includes computer and network hardware, middleware and necessary software. Time accessibility of relevant information is vital for economic development of any country. The improvement of economic activity can be brought by improving capacity in terms of enhancing access to information, while also the technical nature of economic activities required that the knowledge of users are constantly updated which can be achieved through their enhanced information seeking behavior by the use of ICTs. Moreover, use of ICTs lead to innovation which further lead to the enhancement of economic growth and human resource development. Thus, the present paper highlights the role of information technology on economic development of the country as a whole. A period of fifteen years is considered for the study Information and Communication Technology index and Economic Development index has been constructed on the basis of Principal Component Analysis. A simple linear regression has also been conducted to examine the impact of ICT on Economic Development in India. Stationarity of the data set are also checked with the help of appropriate unit root testing technique such as Augmented-Dickey Fuller test. The result shows that there has been considerable impact of ICT on Economic Development in India. Policy suggestions are also given on the basis of the findings of the study.
Time-Table to Mobile Reminders

‘Time–table to Mobile Reminders’ is an Android software aimed towards faculty and student use in schools, colleges and other institutions. The idea to built this app arose because in an education institution keeping track of timetable becomes an tedious job for the teachers and students as well. In order to tackle this problem we decided to built an app that would automate the reminders without any hassle, the only input has to be an image of the time-table. This project is divided into four modules. This includes capturing the image of the time-table, scanning and extracting text from the image using OCR with the help of OpenCV and Tesseract, Identifying the text stored in excel file and classifying it into date, time and lecture, and then Setting reminder accordingly in the app itself. In this way, the faculty or the student will receive a notification on their device a few minutes before the lecture is about to commence without having to look for physical timetable or even digital for that matter every time.
Book Review

This study examined the Twitter streams and websites of 36 university innovation centers and identified 14 service categories the centers offered. Exploring the present Twitter use practices of innovation centers and the services the centers provide can inform the design and planning of service offerings at new innovation centers and support training for center staff in the use of this social media platform. In addition, existing innovation centers can benchmark their service offerings against those services. Furthermore, mapping the services the innovation centers offer to the activities in an innovation workflow model can help center managers optimize the information architecture of their websites and resource guides. In this way, students can easily be informed about the help and resources available for each activity or phase of the innovation process. A comparison of the tweet categories identified in the present study with those of academic libraries assembled in a previous study revealed significant overlap, but some differences as well. In contrast to the Twitter accounts of academic libraries, the Twitter accounts of innovation centers did not tweet about their information services even if they offered them. Innovation centers also did not use Twitter to provide Q&A services to their users. Furthermore, innovation centers tweeted not only about the technological resources they provided, but also about the human resources they recruited to serve as student mentors and advisors. Finally, technology use was more mediated in innovation centers than in libraries, and some centers offered their users fee-based assistance from professionals with their 3D design and printing tasks.
Data Collateral in Cloud Enumerate using AES under Heroku Cloud

Before some years the dossier gets stored using the hardware devices with the sufficient amount of emporium. As of the technology gets improved the emporium can be done in the nebula without the need of the external devices. But the dossier which is gets stored in the nebula that gets fetched by the third-party affiliates. So, to make the system much secured and safety new technique has been proposed in this paper. The paper shows the use of the herokucloud. The herokucloud act as a separate nebulascaffold and the AES contrivance has been used to secure the dossier in the nebula. This technique has been used in various web developing application. They can be used for various collateral maintains of dossier in the anamnesis allocation groove. The main aim of the system is to make secured of the nebuladossier.
Computational linear algebra

This third edition of Braun and Murdoch's bestselling textbook now includes discussion of the use and design principles of the tidyverse packages in R, including expanded coverage of ggplot2, and R Markdown. The expanded simulation chapter introduces the Box–Muller and Metropolis–Hastings algorithms. New examples and exercises have been added throughout. This is the only introduction you'll need to start programming in R, the computing standard for analyzing data. This book comes with real R code that teaches the standards of the language. Unlike other introductory books on the R system, this book emphasizes portable programming skills that apply to most computing languages and techniques used to develop more complex projects. Solutions, datasets, and any errata are available from www.statprogr.science. Worked examples - from real applications - hundreds of exercises, and downloadable code, datasets, and solutions make a complete package for anyone working in or learning practical data science.
A new quantum evolutionary algorithm using dynamic rotation angle catastrophe for knapsack problem

In this paper, a quantum evolution algorithm (IQEA) based on dynamic rotation angle catastrophe technology is proposed to solve the knapsack problem. A quantum revolving gate operator with adaptive dynamic adjustment of the rotation angle is designed according to the evolution generations and fitness values. The population is divided into three parts equally, while preserving the optimal solution for each generation. Using the quantum rotation angles of different periods in the evolution process, the catastrophe operations of these three parts are carried out and the parallel evolution of four types of individuals is realised. With the guidance of better individuals, multi-path optimisation is performed to improve the parallelism of the algorithm. Effectively increase the diversity of the population, carry out multi-directional search and also retain the excellent information in the offspring population, ensuring the stability of the population. Experimental results show that the proposed algorithm is superior to traditional evolutionary algorithms and traditional quantum evolution algorithms.
An Intelligent System for Detecting Image Spam based on Exploration of Text Information Embedded into Images

Spam mails act as a immense hazard to communication security as it leads to phishing or virus attacks that could harm the user accounts and the organizations by exposing confidential information.With these inferences, the present research attempted to accurately detect image spam e-mails which have always been a topic of great research in data security. Detection of image spam mails is divided into two separate components- character segmentation and character recognition. While the former segments individual characters, the latter overcomes the issue of blocked texts and not well surveyed. The final phase of the work is a complete image spam detection system with the two proposed works built to detect spam messages. Various techniques have been proposed to tackle this setback and the principle of this paper is to evaluate and review several algorithms, talk about benchmark statistics or data, show appraisal of performance followed by potential direction for future work.
Implementation Model Linear Regression, Neural Network and Support Vector Machine in Simple Mathematical Pendulum Experiments to Determine the Value of Gravity

machine in mathematical pendulum experiments to find the value of gravity. There were 4 data obtained from mathematical pendulum experiments which were then interpolated to obtain more data (13 data), then the data was used as training data for each model. Each model is tested to get a gravity value of 26 including training data, then compared with reference gravity values [17,18,19]. The results of the model Neural network proved to be the most accurate with an error value of 2.53%. The support vector machine model is the most accurate model with a standard deviation value of 0.03 and the error deviation of 0.058 is the smallest value of the three models in this paper.
Financial Fraud Detection Mechanisms to Overcome Trust Issues within Trade Segments

Frauds in modern era are cause of concern in almost every field of life. Credit card, money laundering and bank frauds are common and technology has to play important part in overcoming this issue. This paper provides insight into financial frauds leading from malicious users in trading network. To this end several techniques are researched over. To start with price based fraud detection is discussed and then similarity matrix, linear binary patterns, support vector machine and random forest in the field of fraud detection are elaborated. This paper highlights pros and cons of each of such techniques. Dataset required determining classification accuracy of these approaches is synthetically driven. Execution time while determining frauds is critical entity and similarity matrix approach is fast and accurate as compared to random forest, support vector and linear binary patterns. Parameters: Classification Accuracy, Execution time Implementation tool: Matlab 2018 Achievement: support vector machine results are closer to similarity matrix based approach in terms of classification accuracy but execution time of similarity based approach is much less and hence this algorithm is considered better in determining financial frauds.
Image block encryption integrating hyper-chaotic system and neural network mechanism

a new image block encryption integrating algorithm based on four-dimensional hyperchaotic system and neural network mechanism is cnstructed. Firstly, a hyperchaotic system is proposed, which combines with cloud model, meanwhile generates a series with better randomness as key stream. Then key stream, neural network mechanism and Feistel block strueture are combined to encryption the image. Finally, the experimental results show that the algorithm has good security.
Image Clustering using K-Means on Marine Products

In this study, the researcher collected 360 marine product images consist of red snapper, prawn, silver belly, pomfret, mackerel, cuttle fish, lobster, crab and sardine to conduct try-outs at first. Secondly, images are separated from background for processing. Then from the images features are extracted via Gray Level Concurrence Matrix. Finally images are clustered according to its groupings by K-Means clustering algorithm. Since marine products are consumed by most of populaces regularly because of its health benefits, availability of nutrients and low cost. For that reason all and sundry can buying. This research helps to identify them by their physical appearances. Marine products have eye-catching altered physiognomies which are cherished to extricate and conclude a specific category. These physical appearances comprise of size, shape, texture, and color. This research succeeds 83% accuracy for bunch the images into nine clusters.
Egypt – EBRD Support

Africa Research Bulletin: Economic, Financial and Technical SeriesVolume 56, Issue 12 p. 22833C-22833C Policy and Practice Egypt – EBRD Support First published: 05 February 2020 https://doi.org/10.1111/j.1467-6346.2020.09304.xRead the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume56, Issue12February 2020Pages 22833C-22833C RelatedInformation
Waste Sorting Mobile Application for Interactive AI Based Waste Management System

A lot of us are misinformed about trash and how it can be managed. We don’t know what kind of trash can be repurposed or be turned into usable items such jas manure. We tend to throw everything out together without segregating at the source of generation. Through our app, they can simply point towards objects and understand what to do with that trash. The goal is to sensitize people not only to segregate trash but also reduce their waste regeneration through practices like composting and reusing. We should first try to understand the plight of waste management in India and how it can be made better. In this project, we will create a mobile app, Python Server with Flask, and Watson Visual Recognition. This mobile app sends pictures of waste and garbage to be analyzed by a server app, using Watson Visual Recognition. The server application will use pictures of common trash to train Watson Visual Recognition to identify various categories of waste, e.g. recycle, compost, or landfill. The resultant smart dustbin is very effective as people have an urge of curiosity and after learning more about their waste, they always tend to make the right decisions. We aim to make a difference in the society through our app and help in making a cleaner and better tomorrow.
Barcode Image Restoration for Recognition of Product Information

Barcode attached on product is to transfer information to users. In practice, many barcodes are degraded over time and they are difficult for users to recognize product information. Therefore, barcode image restoration plays an important role due to clearly showing product information for users. This paper proposed a restoration approach of barcode- EAN 13 images with different degraded characteristics such as vertical lines, blurring, dashed lines. In particular, the degraded barcode images are pre-processed for restoring before recognition, in which a radon method is applied for rotating barcode image and an Otsu segmentation method is employed to split the barcode image from an original image. Therefore, bars in each barcode image are determined for recognition of the correct barcode. Barcode image datasets are collected from different practical products with different quality for restoration before recognizing them. Experimental results show to illustrate the proposed approach for the barcode recognition is the effectiveness