Reviewerly/exHarmony huggingface dataset:
DSU: An On-Device Deep Screen Understanding Framework

User always struggles in getting required information on smart phone. He / She has to go through multiple steps in fetching information from same or previous screens, in scenarios such as replying to messages, inputting phone number, account number, address etc. One of the ways to give a hassle free experience to the end user is, by providing relevant suggestions at the right time by understanding the intention. To derive the appropriate suggestions, it is very important to process only the right amount of information consumed by the user on his screen. In this paper, we are introducing Deep Screen Understanding (DSU) - algorithms and framework for a structured interpretation of screen content. We utilize Android Content Capture framework to capture the screen content, we explain about, interpreting the content in different category of screens and classifying various UI elements. In the first part of the paper, we discuss algorithms for Conversation Screen Understanding. This includes identification of conversation screens and understanding conversation screen information such as recipient info, message type (sent/received), conversation titles etc. This explains generic method and algorithm for interpreting other screen categories such as Browser, Shopping/Product, Media playback screens and so on. In the next part of the paper, we discuss about algorithm for field classification of input edit text fields. These classified fields will be used to provide suggestions from screen understanding module. Classification module identifies input field types of Personal information, Location, and Banking categories. The algorithm can process a screen with <25 ms response time on device, and further measures the accuracy of ∼96% for classifying more than 150 fields in top 50 apps.
Intents4Bot - A Flexible Architecture to Capture User Intentions from Dialogue Systems

The capture of user intentions is a cutting-edge technique that can significantly contribute to improving the user experience in dialog systems. However, the construction of solutions to capture user intent comes up against a plethora of techniques and frameworks with different purposes and levels of effectiveness. This makes building user intent capture solutions a challenging task. To deal with this problem, this work aims to present a flexible architecture for the development of solutions for capturing user intentions in the context of dialog systems.
The Elastic Stack Ability Test To Monitor Slowloris Attack on Digital Ocean Server

Servers have a central role in computer network. The server is in charge of serving user requests with various types of services. Every server activity in handling these things will generate different types of logs. Information from this large amount of logs is often ignored and has not been widely used as material for analyzing the performance of the server itself. In this study, Elastic Stack is functioned as a system that handles upstream to downstream processes starting from collection, transformation, and storage as well as graphical visualization of the Nginx web server given an attack scenario in the form of massive incoming connection requests and server login access attempts. The Elastic Stack components used as log collectors are Filebeat and Metricbeat for system metric data. For testing attacks using the Slowloris tool which will consume web server resources. The results of the research that have been carried out are when there are 500 incoming connections, the web server can serve requests normally, at 1000 connections there are some packets that are not served, the server becomes unable to access when it reaches a total of 2000 incoming connections. Metric data in the form of CPU Usage and Memory Usage are affected, although not significantly. Identification of IP Address shows the source of the attack comes from Singapore, according to the domicile of the attacker's computer. All access data in the form of username, time, origin of region trying to enter the server are recorded by the system.
Theoretical channel simulation modeling and software implementation in quantum secure communication

Through the technical means of computer simulation modeling and calculation, this paper systematically studies the influence of different kinds of communication channels on the key indexes such as bit error rate and communication rate of quantum communication system represented by quantum secure communication system. For the theoretical channels such as bit flip channel and phase flip channel, the transformation model of quantum state is analyzed, the mathematical model of actual physical dimension parameter transformation is established, and the software is designed and implemented.
The Effect of Education Using Snakes and Ladders Board Game on Healthy Snacks Selection of Elementary School Students

BACKGROUND: Primary school age is the stage where the child is in a formal operational state, where the child is able to think and reason logically and draw conclusions from existing information..&#x0D; AIM: This study determined the effect of education using snake and ladder media (ular tangga) on the selection of healthy snacks in an elementary school students. The effect see on students’ knowledge, attitudes, and behavior. The study used Quasi Experiment, One group pretest and posttest without control group. The research variables were knowledge, attitudes, and behavior of students towards the selection of healthy snacks. This research was conducted in March 2020 at an Elementary School in Makassar City, Indonesia.&#x0D; METHODS: The sampling method was simple random sampling with a sample size of 79 students. Data collection tools were using questionnaires and educational media for snakes and ladders. The analysis was carried out descriptively on each variable with an analysis of the frequency distribution and testing the differences before and after the intervention using the Wilcoxon signed rank test.&#x0D; RESULTS: The result of this study showed that the mean of knowledge about health snack selection among student before education with ular tangga is 6.34 increasing to 7.18 after education with ular tangga. Mean of attitude about health snack selection among student before education with ular tangga is 53.92 increasing to 55.43 after education with ular tangga. Mean of behavior health snack selection among student before education with ular tangga is 9.35 increasing to 9.77 after education with ular tangga. Based on the Wilcoxon test, the p-value is obtained for each variable (p&lt;0.05); knowledge (p=0.000), attitude (p=0.009), and behavior (p=0.001).&#x0D; CONCLUSION: Education using snake and ladder media has an influence on the knowledge, attitudes, and behavior of Elementary School students.&#x0D; &#x0D; Key words: Education, snake and ladder media, healthy snacks, elementary school students, Indonesia.&#x0D; &#x0D;
The Objective Deformation Component of a Velocity Field

&amp;lt;p&amp;gt;According to a fundamental axiom of continuum mechanics, material response should be objective, i.e., indifferent to the observer. In the context of geophysical fluid dynamics, fluid-transporting vortices must satisfy this axiom and hence different observers should come to the same conclusion about the location and size of these vortices. As a consequence, only objectively defined extraction methods can provide reliable results for material vortices.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;As velocity fields are inherently non-objective, they render most Eulerian flow-feature detection non-objective. To resolve this issue, &amp;amp;#160;we discuss a general decomposition of a velocity field into an objective deformation component and a rigid-body component. We obtain this decomposition as a solution of a physically motivated extremum problem for the closest rigid-body velocity of a general velocity field.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;This extremum problem turns out to have a unique, &amp;amp;#160;physically interpretable, &amp;amp;#160;closed-form solution. Subtracting this solution from the velocity field then gives an objective deformation velocity field that is also physically observable. As a consequence, all common Eulerian feature detection schemes, as well as the momentum, energy, vorticity, enstrophy, and helicity of the flow, become objective when computed from the deformation velocity component. We illustrate the use of this deformation velocity field on several velocity data sets.&amp;lt;/p&amp;gt;
Implications of Learning About Japanese Language and Culture for the Japanese Department Alumni Living in Japan

&#x0D; &#x0D; &#x0D; Working in Japan is one of the goals of students in the Japanese Department, due to Japan’s strong appeal. Is the material learned in this department enough to help the alumni diaspora in living their lives? The purpose of this study was to describe the implications of learning about the Japanese language and culture for the lives of the alumni of the Japanese Department living in Japan. Qualitative descriptive methods were used, with data collected through questionnaires. The analytical technique used was interpretative description. The results found that the language and culture learned during the lectures was quite helpful in living in Japan. The speaking courses (kaiwa) were highly used. Furthermore, the materials provided in the courses on Japanese grammar (Bunpo), Japanese society, public communication, management and work ethic, as well as conversation, were felt to be very helpful in living in Japan. This was evident from the understanding of the Japanese language used by diaspora alumni in communicating with Japanese people. In addition, the alumni diaspora did not experience obstacles in living in Japan. From these findings it can be concluded that learning about Japanese language and culture was very helpful for the alumni diaspora living in Japan.&#x0D; Keywords: implications, learning, diaspora, alumni&#x0D; &#x0D; &#x0D;
Target Search Based on Scene Priors

Aiming at the problems of reinforcement learning algorithm in target search tasks, such as low accuracy and low fault tolerance, this article mainly introduces a method of reinforcement learning target search based on scene prior in simulation environment.This method mainly uses graph convolutional neural network to extract the current object relationship as the input of prior knowledge.Secondly, it uses the actor-critic algorithm to take the agent's vision, position and prior knowledge as input to decide the agent's next navigation.Finally, use path planning to navigate to the target point to find the target.Through experiments conducted in Habitat and compared with the previous algorithm, the experiment shows that this method is better than the previous algorithm in target search accuracy and navigation efficiency.
NEO-NDA: Neo Natural Language Data Augmentation

Data augmentation generates synthetic data by making changes in data already obtained. It is applied to distinct data types like images, audio, and text. For textual data augmentation, many works propose restrictive transformations, for instance, they only work with one language (monolingual) or create samples with a fixed length [1]–[4]. In this work, we propose NEO Natural language Data Augmentation (NEO-NDA), a more comprehensive tool able to address data generation and rebalancing datasets. It supports data augmentation of minority classes. NEO-NDA is able to work with multiple languages, besides implementing distinct transformations to create new samples. Our results show that NEO-NDA was able to boost the performance of ML models with all datasets evaluated and, in some cases, doubling the performance in comparison with original datasets when no data augmentation method is used.
Editable Blockchain Scheme Based on Shamir Chameleon Hash Secret Sharing

Blockchain has attracted extensive attention because of its decentralized and tamper-proof characteristics. However, with the vigorous development of blockchain, problems also follow. Once the data is stored in the blockchain, it cannot be tampered with, making the blockchain an extrajudicial place for low-cost cybercrime. Criminals use the blockchain to store pornographic, attack scripts, dark network service addresses and other lousy information; Even if the blockchain is used commonly, it will encounter a series of problems, such as that malicious transactions cannot be eradicated and wrong transactions cannot be modified. Therefore, the editable blockchain scheme under specific conditions has broad application prospects. This paper proposes an editable blockchain scheme based on Shamir chameleon hash key sharing. Using the characteristics of chameleon hash, the overall structure of the edited blockchain is not affected. Shamir key sharing algorithm can ensure that each editing is the collective will of nodes. Simulation results show that this scheme has higher security and compatibility than similar schemes.
Deep Networks for Classification

Connecting theory with practice, this systematic and rigorous introduction covers the fundamental principles, algorithms and applications of key mathematical models for high-dimensional data analysis. Comprehensive in its approach, it provides unified coverage of many different low-dimensional models and analytical techniques, including sparse and low-rank models, and both convex and non-convex formulations. Readers will learn how to develop efficient and scalable algorithms for solving real-world problems, supported by numerous examples and exercises throughout, and how to use the computational tools learnt in several application contexts. Applications presented include scientific imaging, communication, face recognition, 3D vision, and deep networks for classification. With code available online, this is an ideal textbook for senior and graduate students in computer science, data science, and electrical engineering, as well as for those taking courses on sparsity, low-dimensional structures, and high-dimensional data. Foreword by Emmanuel Candès.
SENTIMENT ANALYSIS OF REKSADANA ON BIBIT APPLICATIONS USING THE NAÏVE BAYES METHOD AND K-NEAREST NEIGHBOR (KNN)

The public's lack of interest in the capital market has made the top brass of capital market companies compete with each other to provide services in order to provide convenience for customers in the various services available and provide convenience in accessing financial information. The emergence of several startup companies that provide mutual fund investment products for investors, namely PT Bibit Reksadana Grow Together, which created a mutual fund application, namely Bibit Mutual Fund with more than one million users based on data downloaded on the play store by PT Bibit Grow Bersama which acts as a Mutual Fund Selling Agent (APERD) and sells 134 mutual fund products. So, to provide information to the public, it is necessary to have a sentiment analysis on how the opinions of users of the mutual fund seed application use the methodK-nearest neighbor (KNN) and Naïve Bayes, with the results of crawling data of 3800 tweets and scraping of 5000 reviews, then the text processing and labeling stages are carried out using the textblob library, with a high level of accuracy in the classification of tweet data and review data using the K-nearest neighbor method. Nearest Neighbor as much as 88%, 100%, and Naïve Bayes as much as 100%, 100%, it can be concluded that positive opinions from seed mutual fund users are more than negative sentiments.
Digitalization and Digital Culture in the Context of Inclusive Higher Education

The article discusses the current problems of the introduction and implementation of digital education in an inclusive university. Analyzed concepts of digitalization, digital culture and digital technologies. Presented results of an empirical study aimed at identifying the impact of the Internet on students of an inclusive university. The study uses diagnostic methods aimed at studying the activity of a person in a virtual social network, as well as methods of mathematical statistics. The diagnostic results indicate that the majority of students are quite dependent on Internet resources, but this does not prevent them from socializing in society, meeting their needs in interests and communication. There is a direct correlation between the level of quality of education received by students with disabilities and the degree of their participation in society. So, the creation of a digital educational environment in the university provides an opportunity to receive high-quality professional education, which is a socially significant factor affecting the innovative development of the country.
Rule-based design and 2D-analysis of a hybrid system

The three tank switched server arrival system discussed by Chase, Serrano and Ramadge has been cited by many other authors as an interesting example of a hybrid dynamical system. In this process refilling of a tank is started as soon as the tank gets empty. The restrictive assumption that the net flow out of the three tanks be constant and equals the net flow into the tanks will be dropped. A rule basis redesign has been proposed for a three tank switched server arrival system with some more realistic assumptions than in previous work on this subject. Since the flows out of the tanks are arbitrary within given bounds, so are the levels of liquid.
Mathematical Foundations of Machine Learning

Machine learning has achieved remarkable successes in various applications, but there is wide agreement that a mathematical theory for deep learning is missing. Recently, some first mathematical results have been derived in different areas such as mathematical statistics and statistical learning. Any mathematical theory of machine learning will have to combine tools from different fields such as nonparametric statistics, high-dimensional statistics, empirical process theory and approximation theory. The main objective of the workshop was to bring together leading researchers contributing to the mathematics of machine learning. A focus of the workshop was on theory for deep neural networks. Mathematically speaking, neural networks define function classes with a rich mathematical structure that are extremely difficult to analyze because of non-linearity in the parameters. Until very recently, most existing theoretical results could not cope with many of the distinctive characteristics of deep networks such as multiple hidden layers or the ReLU activation function. Other topics of the workshop are procedures for quantifying the uncertainty of machine learning methods and the mathematics of data privacy.
The Recipes for Earth Sciences Go Trilingual: MATLAB, Python and Julia

&amp;lt;p&amp;gt;It&amp;amp;#8217;s been almost 30 years since I started with MATLAB, coming from FORTRAN77, and at a time when Python was still in its infancy and 20 years before Julia was developed. However, I recognize the popularity of Python, including the growing prevalence of Julia, and find that a bilingual and trilingual version of my MATLAB-based books and my courses could be beneficial. I&amp;amp;#8217;ve been learning Python for a few months now, with the goal of writing a Python version of my first book, MATLAB Recipes for Earth Sciences, 5th Edition (Springer 2021). In the meantime, almost all chapters of the book, with topics such as time series analysis, signal processing, digital terrain analysis and image processing, have been translated from MATLAB into Python, some also into Julia. Using the trilingual code in a master's course shows an unexpected but extremely positive side effect: students get away from a particular software or programming language, and focus instead on the method they want to implement. In addition, solutions often use mixtures of programming languages, exploiting the advantages of each. This is an advantage, also helps a lot to produce sustainable and reproducible code. Furthermore, this approach makes the students fit for a job in academia or industry, where other software tools are used than the ones we use in class. Here, I will share my experiences with courses on data analysis in earth sciences with 2&amp;amp;#8211;3 programming languages and with translating a data analysis book from one to another programming language.&amp;lt;/p&amp;gt;
Mining Co-location Patterns in Incremental Spatial Databases

An incremental database can be widely used in many areas due to the changes in data over time, including the location-based services (LBS), environmental ecology, and also the business behavior patterns. Looking for the spatial co-location pattern that appears frequently nearby over an incremental database has become an interesting and essential topic. Many spatial co-location pattern mining approaches are for traditional spatial databases. Therefore, they do not need to consider candidate instances generated and update their participation index in the process. Yoo et al. have proposed the EUCOLOC algorithm to mine co-location patterns in the incremental database. The EUCOLOC algorithm not only needs large storage to store points in the database and their relationships with each other, but also generates many unnecessary candidate instances. In this paper, we propose an approach to mine the co-location patterns for incremental database. Our approach can avoid generating non-incremental candidate instances and non-clique instances. Moreover, we also avoid storing the duplicated data. From our experimental results, we show that our method performed more efficiently than the EUCOLOC algorithm.
Application of quaternion in 3D splicing of total station free setting station

In the precision engineering measurement, the total station is often used for free station measurement, and improving the accuracy of stitching the measurement data of each station is the premise of widely used total station measurement by free setting. This paper is based on the quadratic method to study the stitching method of data measured by total station with free set-up stations. The total station data is obtained by free setting based on the quaternion method, and the method of stitching the data is investigated. Taking the deformation monitoring of the wooden tower in Yingxian County as a case study, a total station was measured by free setting, and the quadratic algorithm was used to realize the coordinate conversion between stations by point name matching, which is comparable to the stitching results of Leica's Cyclone software. In this paper, the improved quaternion algorithm is applied to the free station splicing of total station with the features of fast matching, coarse difference detection and rejection, optimization of redundant observation of the same name point splicing algorithm, inclusion of splicing error correction, and high splicing accuracy.
PERENCANAAN ARSITEKTUR ENTERPRISE PADA PENYEMPURNAAN APLIKASI SITMAPAS RUMAH SAKIT KRAKATAU MEDIKA

SITMPAS is a Patient Management Information System used by Krakatau Medika Hospital, Cilegon. The features in SITMAPAS include patient administration, Outpatient, Inpatient, Operative Medical Support, Non Operative Medical Support, Service Support, Pharmacy and Medical Records, and Logistics. Some of these features are often disturbed and some functions are not in accordance with user needs, resulting in disrupted service processes, due to the absence of development planning in advance in the face of the current industrial 4.0 era. With these problems, this study aims to design architecture from the business, data, application and technology side using the TOGAF ADM method. The use of the TOGAF ADM method will produce a blueprint document for information architecture systems in the development of information systems to support the needs of the Krakatau Medika Hospital. The application of the TOGAF Architecture Development Method (ADM) method is able to identify needs so that it can analyze Fit/Gap and evaluate the SITMAPAS application business process and can propose an imperfect business process, namely the New KHS to produce better performance in targeting organizers from Krakatau Medika.