Reviewerly/exHarmony huggingface dataset:
Web search model for Automatic Annotation of Tweets in Opinion Mining

In sentiment analysis, annotation is the crucial step of data processing to label the review or sentences as positive, negative, or neutral. An annotation process is usually performed by three key approaches: (i) manual, (ii) crowdsourcing, and (iii) automated annotation. Manual annotation is preferred in most of the literature’s and crowdsourcing tools are used in some of the works. This indicates that there is a scarce of automatic annotation and its service is highly essential to support more systematic research in sentiment analysis. Manual procedures mostly depends on external annotators, resulting in costly and time-consuming processes. Thus, we propose a method for automatic annotation using web search model to dynamically label reviews (positive, negative, or neutral) that are not available in the dictionary. Some research works consider the product opinions from e-commerce sites where most of the texts may not be available in the dictionary, in such cases, the web search model can be used instead of manual annotation. A large-scale opinosis dataset is used to evaluate the accuracy of the algorithms and feasibility of the model. The experimental results indicate that this model outperforms conventional methodologies and therefore we firmly believe it will be useful for current researchers in the field of opinion mining.
Text Based Restaurant Recommendation System using End-To-End Memory Network

With growing use of online content streaming websites, online shopping, and other exclusively online services, it becomes more and more imperative for technology companies to invest a lot of funds into a system to gauge user needs and requirements. To bridge this gap, there has been an influx of recommendation systems in the markets. From advertisements, to movies, and products we buy, recommendation engines are feeding on new data everyday to learn user trends. This paper tries to focus on improving the text based recommendation systems that can be implemented to leverage the vast review data that can be found on websites. We suggest using a novel memory based end-to-end network mechanism to reduce the need for long term dependencies and to reduce the need for memory intensive systems. As we generate more and more reviews and textual data on the web everyday, we need to be able to use this data to make meaningful analytical and business predictions. With the ability to perform multiple lookups, implement attention mechanism and back-propogation, this system was found to perform much better when compared to CNN, RNN and LSTM alternatives in our testing.
Literature, Data, Transition Path, and Causality

The chapter develops the stylized facts used in the following three chapters and surveys the literature on the effect of development on democracy and on the effect of democracy on development. The main dataset is the Polity P-index with 7,142 annual observations covering 1960–2016 in the Main sample and 818 in the OPEC sample. The chapter also considers the two political indices from Freedom House. The transition curves for the three political indices are beautiful. The transition curves are robust, with the OPEC-exception. The variability of the political system vanishes with development in accordance with the End of History hypothesis. The causality tests show that increased income causes democracy with little simultaneity only. This finding is robust over 200 years.
Multiprotocol Label Switching

A book on modern network technologies is not complete without a discussion on Multiprotocol Label Switching (MPLS). This chapter provides an overview of MPLS and covers how to configure and troubleshoot it. It also discusses protocols that commonly use MPLS for their underlying transport.
Technician-Technologist Teamwork: Multifunctional Collaboration on Industry Projects

developed and is now the director of the Manufacturing Engineering Technology program.Her primary interest area is at the intersection of manufacturing engineering and statistics involving lean, continuous improvement, and quality
Performance comparison of asymmetric cryptography (case study-mail message)

Data encryption is well known as essential for today’s technology. ElGamal encryption and RSA algorithmis made before storing mails to mail server. ElGamal decryption and RSA decryption is made after retrieving mailsfrom mail server. This system is implemented to secure mail server system for local government’s important mailmessages. These algorithms consume a considerable amount of time and resources of memory, CPU time, andcomputation time to encrypt and decrypt data. This paper discuss the results comparison of these algorithms in termof encryption time, decryption time, and memory usage over variable file sizes. The results show that RSA does fasterencryption process in compare with ElGamal. However, ElGamal decryption process is quicker than RSA. This systemis also expressed comparison of storage Size between RSA and ElGamal. Both of these algorithms are cryptographicpublic-key algorithms but have roles in different techniques. This system is using C# programming language and SQLServer to store mail messages.
Sistem Pakar Untuk Mengidentifikasi Hama Dan Penyakit Pada Tanaman Apel Menggunakan Metode Dempster Shafer

In this study, the identification of pest and disease attack on apple plant on with case study in Balitjestro. The problem faced is the difficulty of determining the information of pests or diseases that attack on apple plants that must meet an expert directly, it takes a long time and cost. The purpose of this study is to accelerate the information obtained from the identification of pests and diseases of the apple plant and its solution without having to meet an expert. Types of pests and diseases that is in pests are Green Lice, Mites, Trips, Leaf Cats, Leaf Sucking Insects, Black Leaf Caterpillars and Fruit Flies. In the disease there are Flour Powder, Leaf Spot, Upas Mushroom, Cancer and Rotten Fruit. From pest and disease data, all symptom data is 38 data. To get the information, made Expert System. Expert system in this study to determine the results of identification using Dempster Shafer calculation method. Demster Shafer is one of the mathematical theories used to perform a proof that is based on the function of trust and also logic makes sense. At the test stage yields an accuracy value of 100%. However there is one test of the expert only producing one and the results of the system show more than one. But one of the results given by the system is the same as the result given by an expert, then it is justified.
Hidden Markov Model

This textbook introduces fundamental concepts, major models, and popular applications of pattern recognition for a one-semester undergraduate course. To ensure student understanding, the text focuses on a relatively small number of core concepts with an abundance of illustrations and examples. Concepts are reinforced with hands-on exercises to nurture the student's skill in problem solving. New concepts and algorithms are framed by real-world context and established as part of the big picture introduced in an early chapter. A problem-solving strategy is employed in several chapters to equip students with an approach for new problems in pattern recognition. This text also points out common errors that a new player in pattern recognition may encounter, and fosters the ability for readers to find useful resources and independently solve a new pattern recognition task through various working examples. Students with an undergraduate understanding of mathematical analysis, linear algebra, and probability will be well prepared to master the concepts and mathematical analysis presented here.
Kansas Field Research 2020

The Kansas Mesonet is a state-of-the-art environmental monitoring network that provides accurate rainfall measurements across Kansas.However, missing rainfall records are common problems in weather stations that rely on tipping bucket rain gauges.In this study, we conducted a pilot experiment to estimate missing rainfall records from root-zone soil moisture information recorded at Kansas Mesonet stations.Soil moisture is recorded at depths of 5, 10, 20, and 50 cm using the Campbell Scientific CS655 soil water reflectometer.Hourly rainfall and soil moisture data from mid-August 2017 to mid-May 2018 were taken from three stations (Lakin, Manhattan, and Hays) of the Kansas Mesonet.Rainfall was estimated as the difference in soil moisture storage between 1 hour before and 1 hour after a given rainfall event.Preliminary results show that soil moisture-derived rainfall can be more accurate than using rainfall data from nearby stations.Soil moisture could serve as very useful information in quality control procedures to flag missing rainfall events.
The Use Of Jigsaw Strategy To Improve Students' Reading Comprehension Achievement At SMKN 1 CANDIPURO

The objectives of this research are to find out the improvement of the students' reading ability before and after the implementation of jigsaw strategy and also to identify student perception about the use of jigsaw strategy at SMK N 1 Candipuro. This research was a quantitative research and the method was one group pretest and post-test design. The reading test was administrated as the instrument in this research. In pre-test, students mean score was 53. 86 while in post-test it increases to 65.46; the gain obtained in pre-test to post-test is 11.59. The analysis of SPSS 20 shows that there is improvement of students' reading ability after the implementation of jigsaw strategy; Based on seeing the analysis of students' work in pre-test and post-test on each aspect of reading. It could be found that determining main idea was the aspect that increased the most. Keyword: Jigsaw strategy, Reading
An Efficient Text Image Elimination App for Android

Smartphone sales are at an all-time high with the ever increasing use of smartphones, we have access to data like never before. But with information that vast, we often get suffocated by the images that clutter our devices, making it that much harder to get to the pictures that matter to us. With the power of Machine Learning and image processing, this Text Image Elimination App will free your device from all the clutter and make your life easier. The application removes the images they may not want on their phone. Images containing text will be processed and the text extracted from the images will be compared to a list of texts given by the user and if there is any instance of the text in the image it will automatically be deleted. This paper proposes an efficient android application where the user can optimize the storage space by eliminating the images of his interest based on text matching without directly going in to the directory.
Atividades virtuais do projeto de extensão horta terapêutica/ Virtual activities of Therapeutic Garden extension project

During the suspension of the face-to-face activities, the "therapeutic garden" extension project developed by the Federal Catarinense Institute (IFC) Campus Videira, together with the Psychosocial Support Center (CAPS), had to resort to the use of digital media to continue the actions and adapt to this new and challenging scenario.The work aims to report the use of digital media as a means of disseminating the extension project
Loading Data into Big Data Clusters

With our first SQL Server Big Data Cluster in place, we should have a look at how we can use it. Therefore, we will start by adding some data to it.
Implementation of Instructional Explicit Model toward Writing Skill of Descriptive Text for Junior High School Student

Indonesian language learning Curriculum 2013 which will be studied by junior high school students is one of them is description text. Description text is a type of text describing an object, a thing and a situation so that the reader seems to hear seeing, or feeling the things described. In writing description text, it must pay attention to the structure and rules of language of the description text that have been set, so as to produce a solid and intact description text. In writing the description text students still experience difficulties in writing language rules that are still lacking. The purpose of this study was to determine the effect of using the Explicit Instruction model on the description of writing skills in junior high school students. This type of research is quantitative research using the experimental method. The design of this study was one group pretets-posttest design of this study conducted twice before being given treatment and after being given treatment. The sampling technique of this study was purposive sampling technique, the sample in this study was one class. The data in this study is a performance test results of the description text writing skills before and after using the Explicit Instruction learning model for the description skills of text writing for junior high school students. The results of his research are that there is a significant effect between the learning model and the results of the news text writing skills before and after using the Explicit Instructionmodel on Writing Skills. Text description for Junior High School Students. This is evidenced by the results of research that show that the value of tcount t table ( 1.90), so that H0 is rejected and H1 is accepted. That means the explicit instruction learning model is effectively used in the description writing skills of junior high school students.
Arrays and Loops

An array enables you to work with several data items of the same type using a single name, the array name. The need for this occurs often—when working with a series of temperatures or the ages of a group of people, for example. A loop is another fundamental programming facility. It provides a mechanism for repeating one or more statements as many times as your application requires. Loops are essential in the majority of programs. Using a computer to calculate the company payroll, for example, would not be practicable without a loop. There are several kinds of loop, each with their own particular area of application.
Model Proses Pembelajaran Akuntansi: Peran Teknologi Informasi Dikalangan Dosen Akuntansi Pada Masa Pandemi

Abstract This study aims to test empirically: 1) The role of IT 2) The effect of the accounting learning process 3) Institutional response to Covid-19 on Teaching Performance of Accounting lecturers with Transfer Knowledge as an Intervening Variable, which consists of three independent variables, namely the Role of IT (X1) , Accounting Learning Process (X2), Institutional Response to Covid-19 (X3) with the dependent variable Accounting Lecturer Teaching Performance (Y), and the intervening variable Transfer Knowledge (Z). The source of the data used in this study comes from the answers to the questionnaires distributed to the Accounting Lecturers in Indonesia. The questionnaire was distributed via the geogle link from, the respondents who filled in were 124 people. The analysis technique uses data that includes the outer model, inner model and path analysis with Smart PLS 3.0. The results of this study are that the accounting learning process and institutional responses to Covid-19 have a positive and significant effect on the teaching performance of accounting lecturers and are mediated by transfer knowledge.
Information Systems Security Risk

Information systems security is critically important to organizations, private and public. We need the Internet to contact the world, and have benefited personally and economically from using the Web. But there have been many risks that have been identified in the open Internet environment. A number of frameworks are considered. Some appear in the form of standards, such as from the International Standards Organization. That set of standards provides guidance in the macro-management of information systems security. Frameworks can provide guidance in developing processes to attain IS security, to include a Security Process Cycle and a list of best practices. Supply chains are an especially important economic use of the Internet, and involve a special set of risks. While there are many inherent risks in electronic data interchange (needed to efficiently manage supply chains), methods have been developed to make this a secure activity in well-managed supply chains.
ROBOTIC MOTION PLANNING USING CONVEX OPTIMIZATION METHODS

Iraqi Journal for Computers and Informatics is an open access, double-blind peer reviewed, international academic journal published biannual (since 2017).It is institutional journal issued by the University of Information Technology and Communications (UoITC) in Baghdad- Iraq. IJCI aims to contribute to the constant scientific research and to provide a sober scientific journal that enriches scholars around the world.
Correction to: Review of Landsat False Color Composite Images for Lithological Mapping of Pre-Cambrian to Recent Rocks: A Case Study of Pail/Padhrar Area in Punjab Province, Pakistan

Unfortunately, Fig. 1 was published incorrectly in the original article. Hereby, the correct figure is given below.
A Display-driven Anti-aliasing Visualization Technology of Large-scale Vector Data in Real-time

efficient and rapid visualization of large-scale vector data is a research hotpot in geographic information science (GIS). In existing popular method, the computation increases dramatically as data volumes grows, even with parallel technologies. However, the display-driven computing model (DisDC) greatly improves the ability of visualization of large-scale vector data. In this paper, we proposed a rapid visualization method based on the characteristics of DisDC, efficient data organization strategies and anti-aliasing pixel generation algorithms are designed to supporting rapid visualization and presenting better visualization effects respectively. Visualization results are organized into a tile-pyramid structure to enable stepless zooming. Experiments show that our approach can significantly reduce computation time and provide real-time visualization effects of million-scale vector data while remaining superior visualization effects.
Sarcasm Revealing using Rule Based Algorithm

Sentiment analysis is the process of finding out whether one's opinion is positive, negative, or neutral. Now-a-days the people are telling their opinion about the fields like marketing product, political and social phenomena are mostly through the online. Their opinions are positive, negative or neutral. The machine to identify the opinion is very difficult. There are so many issues in this field. The one of the issue is sarcasm detection. Sometimes the people give their opinion sarcastically. Sarcastic means, an opinion of an object is to say positive instead of negative. The machine will take this opinion as positive. So the final polarity of the product will be wrong due to this kind of identification. The purpose of this paper is to find these types of sentences and correct the polarity value.
DIGITAL ENGINES AT WORK: PROMOTING RESEARCH SKILLS IN STUDENTS

The paper focuses on the digital teaching and research practices which make an indispensable integral component of upscale education. The authors compare traditional approaches to education against the much demanded by the society, promising approaches which heavily rely on the digital engines. Most relevant –education-wise –features of centennials / millennials, also referred to as “digital natives”, are taken into account. The digital teaching practices and digital research practices that can be used in teaching are outlined; teaching and research potential of some digital engines is examined. Corpus-based experiment along with the analysis of search engine results, cultural-linguistic research through Google and Yandex searching, Tropes Zoom’s content analysis and some other methodological novelties that can be used in the classroom as well as facilitate and substantiate the research results are analysed.
XCTest Introduction

This chapter gives an overview of the core features of XCTest, Apple's Swift testing framework, and how to use it to write tests from within Xcode. It walks through the most useful testing assertions, how to test asynchronous code, and how to perform setup and tear down logic common to multiple tests.
Minimizing the Security Risks in Hybrid Cloud Networks with the Aid of Optimal Triple Data Encryption Standard Algorithm

Security is one of the challenging problems in the hybrid cloud, because of the combination of private and public cloud. A novel algorithm has been presented in this paper, to secure the hybrid cloud networks during information storage and recovery. The algorithm consists of four modules: (i) data collection module, (ii) data de-duplication module, (iii) encrypted de-duplication module and (iv) user interface module. Initially, the document is collected using the data collection module and duplicate data is removed using the matching score mechanism. This de-duplicated data is encrypted using the Optimal Triple Data Encryption Standard (OTDES). To enhance the performance of TDES, oppositional monarch butterfly optimization algorithm (OMBOA) is used in hybrid combination with TDES and this is referred as OTDES. This encrypted data is then stored on the cloud. The stored information can be accessed through the user interface module. Performance evaluation of the proposed security system has been carried out on the basis of different evaluation metrics and have been found in good order.
The Impact of Culture on Humorous Ads: An Abstract

Humor in advertising targets a very heterogeneous audience simultaneously on the local and national even international scale. While it is universally practiced, practices of humor are, nevertheless, extremely varied, and its use in advertising may require adaptation when communicating in different contexts (Alden et al. 1993). As advertising is strongly based on the culture of the country (Ozdemir and Hewett 2010), on tradition and on a specific mode of communication (Newman 2004; Tungate 2007), it can register strongly in this context which will impact the understanding and perception of the message it wants to convey and influence consumer behavior and purchasing decisions (Palmatier et al. 2006). Considering this, some advertising campaigns would be totally impossible to export (De Wulf et al. 2001), while others might require some adaptation to suit different cultural contexts (Alden et al. 1993). The question of standardization and adaptation of advertising campaigns on the international scale has been the subject of extensive research (Schmid and Kotulla 2011). However, reviews of existing literature show doubt on the results of the previous research (Birnik and Bowman 2007). In the case of humorous ads, companies are advised to “standardize” in their international communication (Alden et al. 1993) and at the same time to “adapt” their strategies even locally on their national markets (Rutigliano 1986). Considering that the proportion of international advertisements using humorous appeals can reach up to 50% of TV advertising campaigns in the USA, while similar statistics can be observed in other countries and other types of communication (Millward Brown Brand report), and the huge and growing global advertising spending which represented $550 billion dollars in 2016 (McKinsey, Wilkofsky Gruen Associate: © Statista 2017), it appears essential to understand the stimulus of humor in ads tendency with a cross-cultural comparison. The objective of this research is to understand the cultural differences in terms of humor in ads and the influence of culture in the consumer perception and behavior.