Reviewerly/exHarmony huggingface dataset:
English Learning Materials for Restaurant Students at Apollonia Hotel School

This study aims to develop learning materials in the form of books for restaurant students at Apollonia Hotel School Denpasar. The method of the current study is Design and Development. In developing the learning material, this study uses the DnD model by Richey and Klien. There were several processes carried out, namely identifying learning materials needed; developing learning materials in the form of books; and evaluating the results of material development. The results of the study found that there are eight types of material that need by restaurants students namely procedure of handling cleanliness, maintain kitchen and restaurant equipment, renewing local knowledge, provide a link between kitchen area and service area, provide gueridon service, provide silver service, provide food and beverage service, and provide room service. The results of expert tests showed the score of the learning material developed is 85 which belongs to good category.
Visitor Satisfaction Analysis of Library Services at Sultan Agung Islamic University Using Libqual and Fuzzy

Quality of service is part of the services provided by the Universitas Islam Sultan Agung (UNISSULA) library so that it matches the expectations and needs of visitors. There is not yet a system that can be used to measure service quality so that the process of measuring services is less than optimal. So it needs to be made a system that can be used to evaluate the quality of library services. The system was built using two methods in its development, namely the Libqual Method and the Fuzzy Tsukamoto Method by using a Likert scale from values 1 to 5. The Libqual method is used to measure the gap between perception and expectations with two calculations namely Adequancy Gap (AG) and Superiority Gap (SG) , in Fuzzy Tsukamoto there are four process processes, namely fuzzyfication, rule formation, inference and defuzzyfication machines which are used as ranking of each question on the questionnaire regarding service quality. Ranking aims to find out the question items about the quality of service that has the best value on a scale from small to large. The results of calculations using Libqual and Fuzzy Tsukamoto from three dimensions that exist in Libqual, Library as Place gets first rank with a value of 3,31 which is the most optimal service quality.
THE READABILITY OF STUDENTS’ TEXTBOOK USED IN SEMANTIC AND PRAGMATIC COURSE IN ENGLISH LANGUAGE EDUCATION PROGRAM OF UNP

Many students got low score in Semantic and Pragmatic course. They complained that the textbook used in the course is difficult to understand. It is possible to consider that there is a correlation between the students’ bad scores and the readability of the textbook. In previous research, it was found that suitable level of readability and reading skills are important consideration to reach maximum learning gain. Because of that, it becomes important to measure readability level, the factors which influencing readability level and the best way to use the textbook. This research was a descriptive quantitative research. The sample of this research was 3 pages from 3 chapters of the textbook, chapter 9, 10, and 11 chosen randomly from each chapter. The instruments were a written questionnaire, an online readability measurement website, and notes during interview. The findings show that the readability level measured by students and readability formula was difficult. The most influencing factors in determining readability level were interest and vocabulary difficulty. The best way to use the textbook was using one single textbook, editting by put some notes on the page, then presenting it in a lecture form by the lecturer.
Population based Optimized and Condensed Fuzzy Deep Belief Network for Credit Card Fraudulent Detection

In this information era, with the advancement in technology, there is a high risk due to financial fraud which is a continually increasing menace during online transactions.Credit card fraudulent identification is a toughest challenge because of two important issues, as the profile of the credit card user's behavior changes constantly and credit card datasets are skewed.The factors which greatly affects the credit card fraudulent transaction detection are primarily based on data sampling models, features involved in feature selection and detection approaches implied.To overwhelm these issues, instead of using certainty theory, this paper encapsulates with three different empowered models are deployed for intellectual way of fraudulent transaction detection.In this work uncertainty theory of intuitionistic fuzzy theorem to determine the significant features which will influence the detection process effectively.Maximized relevancy among dependent and independent features of credit card dataset are determined using grade of membership and non-membership information of each features.The intuitionistic fuzzy mutual information with the knowledge of entropy it selects the features with highest information score as significant feature subset.This proposed model devised Fuzzy Deep Belief Network enriched with Sea Turtle Foraging for credit card fraudulent detection (EFDBN-STFA).The fuzzy deep belief network greatly handles the complex pattern of credit card transactions with its deep knowledge and stacked restricted Boltzmann machine the pattern of dataset is analyzed.The weights assigned to the hidden nodes are fine-tuned by the sea turtle foraging using its fitness measure and thus it improves the detection accuracy of the FDBN.Simulation results proved the efficacy of EFDBN-STFA on two different credit card datasets with its gained ability of handling hesitation factor and optimization using metaheuristic approach, it achieves higher detection rate with reduced false alarms compared to other existing detection models.
Recent Developments in Dynamic Modeling, Control and Applications of Neural Networks

Recent advances and emerging approaches in neural model and learning (i.e. deep neural network) have led to an unparalleled surge of interest in the topic of neural networks. Neural networks provid...
Differential Privacy and Its Applications in Social Network Analysis: A Survey.

Differential privacy is effective in sharing information and preserving privacy with a strong guarantee. As social network analysis has been extensively adopted in many applications, it opens a new arena for the application of differential privacy. In this article, we provide a comprehensive survey connecting the basic principles of differential privacy and applications in social network analysis. We present a concise review of the foundations of differential privacy and the major variants and discuss how differential privacy is applied to social network analysis, including privacy attacks in social networks, types of differential privacy in social network analysis, and a series of popular tasks, such as degree distribution analysis, subgraph counting and edge weights. We also discuss a series of challenges for future studies.
FEATURES OF THE DEVELOPMENT OF MEDIA EDUCATION IN THE UNITED STATES OF AMERICA

In the article the author analyzed the features of the development of media education in the United States of America.Media education in the USA has come a long way in its development: from film experiments to the founding of the National Association for Media Literacy Education.There are presented content and the list of documents which regulate the development of media education, associations and organizations for media education in the USA.Abilities and skills which children should have for using media are defined.Statistics of Pew Research Center about time which children spend with media is given.The author analyzed concepts "media education" and "media literacy".The article examines several examples of using media educational tasks on different lessons.According to the documents of National Association for Media Literacy Education (NAMLE) principals and aims of media education are defined.The prospects for the development of this problem are shown.
Report Stating the Concept of Cloud Computing Testing and Its Challenges

These days Cloud Computing is in demand and the latest technology used by the organisation to handle large amount of data. This paper will explain the concept of Cloud Computing, its models, advantages, disadvantages and also the challenges. The type of testing use for cloud computing will also be discussed in this paper. The organisations may have their own cloud data centre or also can tie up with other data service providers who provides the facility of cloud computing. The data is shared among various servers and then can be accessed from there. It helps to increase the efficiency of the business organisation.
On the Improvement of 2D Quality Assessment Metrics for Omnidirectional Images

Subjective quality assessment remains the most reliable way to evaluate image quality while being tedious and money consuming. Therefore, objective quality evaluation ensures a trade-off by providing a computational approach for predicting image quality. Even though a large literature exists for 2D image and video quality evaluation, 360-degree images quality is still under-explored. One can question the efficiency of 2D quality metrics on such a new type of content. To this end, we propose to study the possible improvement of well-known 2D quality metrics using important features related to 360-degree content, i.e. equator bias and visual saliency. The performance evaluation is conducted on two databases containing various distortion types. The obtained results show a slight improvement of the performance highlighting some problems inherently related to both the database content and the subjective evaluation approach used to obtain the observers&#x2019; quality scores.
Do FX Interventions Lead to Higher FX Debt? Evidence from Firm-Level Data

Central banks often buy or sell reserves-–-so called FX interventions (FXIs)---to dampen sharp exchange rate movements caused by volatile capital flows. At the same time, these interventions may entail unintended side effects. In this paper, we investigate whether FXIs incentivize firms to take on more unhedged FX debt, thereby increasing medium-term corporate vulnerabilities. Using a novel dataset with close to 5,000 nonfinancial firms across 19 emerging markets covering 2002--2017, we find that the firm-level share of FX debt rises following intensive use of FXIs, particularly for non-exporting firms in shallow financial markets with no FX debt to begin with. The magnitude of this effect is economically significant, with one standard deviation increase in FXI leading to an average 2 percentage points increase in the FX debt share. For reference, the median share of FX debt in the sample is zero.
Data Mining-Based Phishing Detection

Webpages can be faked easily nowadays and as there are many internet users, it is not hard to find some becoming victims of them.Simultaneously, it is not uncommon these days that more and more activities such as banking and shopping are being moved to the internet, which may lead to huge financial losses.In this paper, a developed Chrome plugin for data mining-based detection of phishing webpages is described.The plugin is written in JavaScript and it uses a C4.5 decision tree model created on the basis of collected data with eight describing attributes.The usability of the model is validated with 10-fold cross-validation and the computation of sensitivity, specificity and overall accuracy.The achieved results of experiments are promising.
Goal Oriented Requirements Engineering for Blockchain based Food Supply Chain

Blockchain technology is the buzz word in the industry and research fields and it is considered to be a disruptive technology. Every organization that interacts with agents and intermediaries for getting their business processes are trying to bring Blockchain in their business for the efficiency, security and trust it can bring. The world has started experimenting with blockchain but there are still a lot of basic issues that need attention as the technology is relatively new. The standards and practices for implementing this new technology are not yet in place which impede its full acceptance despite being useful. Blockchain applications have specific concerns like non-repudiation, data privacy, immutable transactions etc. which should be addressed for the implementation of technology. Goal oriented Requirements Engineering is a popular technique that helps in understanding business goals in a comprehensive manner. As a first step towards formalizing the requirements analysis, this paper focuses on identifying the goals and softgoals for blockchain enabled systems. Specifically, a case study on blockchain enabled food supply chain has been explored for identifying the goals and softgoals. These goals can then be used by software engineers or practitioners for requirements specification and system design.
Exponential functions through a real-world context

The exponential function as a mathematical concept plays an important role in the corpus of mathematical knowledge, but unfortunately students have problems grasping it. Paper exposes examples of exponential function application in a real-world context.
Generation of Window-Traversing Flyable Trajectories Using Logistic Curve

This work considers point-to-point flyable trajectory generation through constrained planar regions referred as windows. A four parameter logistic curve trajectory planning tool is proposed for generating feasible trajectories that (i) connect the given initial and final positions with (ii) smooth bounded velocity and acceleration variations (flyability), and (iii) pass through the prescribed windows. A two-step approach is proposed, first narrowing down the search space to a restricted set in six dimensions, parameterizing a variety of trajectories that satisfy the derived closed-form flyability conditions. The final solutions are found by sampling that set using closed-form window traversal conditions. Numerical examples are presented to analyze the performance of the proposed approach in terms of number of solutions and computation time.
A secure cloud service deployment framework for DevOps

&lt;span&gt;The advancements in cloud computing and leveraging the benefits from cloud computing to the service providers have increased the deployment of traditional applications to the cloud. The applications once deployed on the cloud, due to various reasons, need migration from development infrastructure to operational infrastructure, one operational instance to other operational instances due to load balancing and the cycle continues due to the use of DevOps as development strategies for cloud computing applications. Advocates of hybrid and public clouds observe cloud computing makes it possible for organizations to avert or minimize upfront IT infrastructure expenses. Proponents also assert that cloud computing systems permit businesses to receive their software up and running faster, using improved manageability and less maintenance, so it empowers IT teams to rapidly adapt tools to meet the varying and unpredictable requirements. DevOps is a lot of practices that mechanizes the procedures between programming improvement and IT groups, all together that they can fabricate, test, and discharge programming quicker and even more dependably. The idea of DevOps is established on building a culture of a joint effort between groups that generally worked in relative siloes. The guaranteed advantages incorporate expanded trust, quicker programming discharges, capacity to explain basic issues rapidly and better oversee impromptu work. Thus, this work identifies the need for providing multiple security protocols during the complete life cycle of cloud application development and deployment. This work proposes a novel framework for automatic selection and deployment of the security protocols during cloud service deployments. The framework identifies the need for security aspects and selects the appropriate security algorithms for virtual machines. The proposed framework demonstrates nearly 80% improvement over the security policy deployment time. &lt;/span&gt;
Reliability Optimization of Wind Farm Power Systems Using Bat Algorithm with Generalized Flight

In this paper, two metaheuristics, namely the Bat algorithm (BAT) and a recent hybridization of bat algorithm with generalized walk evolutionary algorithm are presented. The bat algorithm and the Bat algorithm with generalized flight (BAG) are used to solve the problem of optimal redundancy design of series-parallel electrical systems. In order to assess the reliability of the heterogeneous system of multi-state series-parallel, the Ushakov method a universal moment generating function (UMGF) is used to allow fast estimation. The design objective is to maximize the reliability of the bulk power generation system from wind farm. The components of each electrical subsystem are characterized by their performance (capacity), cost and reliability. Reliability is defined as the ability to satisfy consumer demand that is given by a cumulative load curve. By comparing three algorithms cited in this study, the results show that the hybridization of Bat and Generalized Evolutionary Walk Algorithm (BAG) are effective in solving the reliability redundancy optimization problem (RROP). Two illustrative examples are presented.
User-Guided Chinese Painting Completion–A Generative Adversarial Network Approach

Image completion models based on deep neural networks have been a research hot spot in computer vision. However, most of the previous methods focus on natural images, such as faces and landscapes. In this paper, we propose a novel image completion model for a special set of artificial ancient Chinese paintings to address this limitation. Specifically, we integrate three complements: the Wasserstein Generative Adversarial Networks (WGAN), Perceptual loss, and Mean Squared Error (MSE) to train the model robustly. We propose a unique generator which can not only pay more attention to complete the details of ancient Chinese paintings but also can provide the synthesized lines to help artists to analyze paintings conveniently. Additionally, we also allow a user to supply a structure hint to guide our model to complete Chinese paintings according to his/her preference. Extensive experiments firmly demonstrate the effectiveness of our approach to complete ancient Chinese paintings and remove abnormal color blocks from them.
A Message to You, Rudy: Hear Reason, or Nature Will Make You Feel Her

ABSTRACT This articles main takeaway is the importance of the question: Why did it take me so much time to realize that the pandemic is real? Cutting across the personal and the collective, the uncanny and the ordinary, the visceral and the rational, this article shows that our philosophies and our sciences lack of sensitivity to instinct and emotion is a problem
Praktikalitas Media Video Tutorial sebagai Suplemen Digital Learning pada Mata Kuliah Persamaan Diferensial Biasa

Industrial revolution 4.0 in which digital technology being more integrated in all aspects of human life will demand the new reform of education world. Not only can it affect the curriculum being taught, but it will also lead to the changes of the methods and approaches in conducting the lesson. One of the changes is the use of digital learning. Universitas Negeri Padang has regulation of conducting lesson through e-learning platform proportionally for all courses, including the course of Ordinary Differential Equation. Ordinary Differential Equation is a mandatory course that should be taken by mathematics department’s students. In order to support students to develop their under standing about the concept and its application while using digital learning method, the researchers develop some tutorial video as supplementary media. Therefore, this study aimed to describe the practicality of the tutorial video. This is a descriptive research where the data were collected using closed questionnaire. The respondents were 39 mathematics students of Universitas Negeri Padang who joined Ordinary Differential Equation Course in the semester of January-June 2020. The result indicates that the video tutorials used in the course are in the category of very practice with the score percentage 86,6%.
A Similarity-Based Software Recommendation Method Reflecting User Requirements

Existing software recommendation methods consider only the usage frequencies of software as far as we know.In this study, we propose a software recommendation method reflecting user requirements based on both the Boolean model and vector space model.A function matrix and function vector are made from the functional specification of each software type and stored in the database.First, it creates a requirement vector from a user's functional requirements of the desired software.Second, it makes a list of software with the same functions wanted using the function matrix based on the Boolean model.Third, the cosine similarities are calculated between the requirement vector and function vectors of the software in the list based on the vector space model.Finally, a software recommendation list is generated in descending order of similarity.Based on the experiment results, appropriate software well suited for user requirements can be recommended.This is because we searched for software that satisfies each user's requirements by using the cosine similarity function of information retrieval and recommended it according to the ranking.In the future, performance can be improved by utilizing statistical search techniques.
Czech parliament meeting recordings as ASR training data

I present a way to leverage the stenographed recordings of the Czech parliament meetings for purposes of training a speech-to-text system.The article presents a method for scraping the data, acquiring word-level alignment and selecting reliable parts of the imprecise transcript.Finally, I present an ASR system trained on these and other data.
Development of a Mecanum-Wheeled Mobile Robot for Dynamic- and Static-Obstacle Avoidance Based on Laser Range Sensor

This study aims to present an idea about the practical consequences of using mobile robots with Mecanum wheels.For mobile robots, an approach is proposed to avoid obstacles without location and map information.This approach is presented using a series of developed solutions.This article shares the process on how a set of discussed conceptual methodologies can be applied as well as their practical results.This method is provided using fuzzy logic and gap tracking.LIDAR is used to recognize obstacles around the mobile robot.By using the LIDAR, the robot detects gaps around it and moves according to fuzzy logic.The fuzzy logic consists of three inputs, an output, and 45 rules.The first of the membership functions represents the membership function that replaces the obstacle.The second membership function calculates the distance to the obstacle.The final login membership function is used to determine the angle between the obstacle and robot view.The output membership function represents the membership function that moves the robot.The results are analyzed under three different scenarios with five different experiments for each scenario.The results show that the mobile robot can avoid obstacles without location and map information.We believe that the proposed method can be used in mobile robots such as guard and service robots.