Reviewerly/exHarmony huggingface dataset:
Wau: A User Authentication System Based on Channel State Information and Deep Neural Networks

Abstract Recently, user authentication techniques have attracted more attention and played a more important role in human-computer interaction applications. In this paper, we propose a user authentication system based on CSI (channel state information) called Wau. This system works in a device-free way and has no privacy violation because it facilitates the crucial characteristics of CSI that the unique CSI variation from different user activity can be measured and recognized. We adopt deep neural networks to realize the authentication of 8 people in three environments, including a through-the-wall scenario. The highest recognition accuracy reaches up to 98%. These results validate the feasibility and effectiveness of the user authentication system using CSI and deep neural networks.
<b>bootUR</b>: An <i>R</i> Package for Bootstrap Unit Root Tests

Unit root tests form an essential part of any time series analysis. We provide practitioners with a single, unified framework for comprehensive and reliable unit root testing in the R package bootUR. The package's backbone is the popular augmented Dickey-Fuller test paired with a union of rejections principle, which can be performed directly on single time series or multiple (including panel) time series. Accurate inference is ensured through the use of bootstrap methods. The package addresses the needs of both novice users, by providing user-friendly and easy-to-implement functions with sensible default options, as well as expert users, by giving full user-control to adjust the tests to one's desired settings. Our parallelized C++ implementation ensures that all unit root tests are scalable to datasets containing many time series.
Implementasi Text Mining Pada Analisis Sentimen Pengguna Twitter Terhadap Marketplace di Indonesia Menggunakan Algoritma Support Vector Machine

&lt;p&gt;In this digital era, technology development has changed the behavior of society from buy offline to online. One of this behavioral changes is marked by the growth of global marketplace including in Indonesia. The big marketplaces in Indonesia that have received a lot of public response on social media are Tokopedia, Shopee, and Bukalapak. This research determines the public sentiment toward both the service and issues surrounding these three marketplaces on media social especially Twitter. Public opinion is classified into a positive or negative sentiment. The data used in this study is obtained from Twitter API (Application Programming Interface) using keyword Shopee, Tokopedia, and Bukalapak. Preprocessing texts are divided into five steps: cleansing, case folding, stemming, stopwords, and tokenizing. Training and testing data are divided using &lt;em&gt;k&lt;/em&gt;-fold cross validation method, while visualization the characteristic of text is using word cloud. Research shows that public are posting tweet more positive sentiment than negative one. The perfomance of classification shows that the best &lt;em&gt;G&lt;/em&gt;-mean and AUC value for Bukalapak testing data are 0.85 and 0.86 in the first fold. While the best &lt;em&gt;G&lt;/em&gt;-mean and AUC value for Shopee testing data are 0.76 and 0.77 in the seventh fold and the best &lt;em&gt;G&lt;/em&gt;-mean and AUC value for Tokopedia testing data are 0.82 and 0.83 in the sixth fold.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Keywords&lt;/strong&gt; : sentiment analysis, marketplace, support vector machine, twitter&lt;/p&gt;
Application of Algorithm with Novel Successive Approximate Registration Method of Medical Image

Abstract Medical image registration is widely used in the clinical field. A simple and effective registration method for medical images is proposed, which is not only used images’ hierarchical information, but also the successive approximate method is used. It mainly includes two steps, which are the coarse registration and the fine registration. In the coarse registration procedure, the couple images’ edge features are extracted. Further more, the contour line features are extracted based on the edge features. The contour lines are selected as registration objects to accomplish the coarse registration based on the Principal Axis method. In the second registration procedure, i.e. the fine registration, the hierarchical information of the images are obtained by the convolution operator and pooling method firstly. Then these information are matched from the last scale to the first scale to obtain the last registration result. The proposed method’s validity is proved by different registration experiments, and the proposed method can also be applied to incomplete images’ registration. The error of registration is less than one pixel unit in the different registration experiments of the proposed method.
Smart Retainers in Orthodontics

Orthodontists often observe discrepancy between what an affected person reports about retainer wear and what a medical examination shows. Retention is the maximum vital issue of treatment frequently omitted through the patients. The orthodontists normally do not have a whole lot of choices but to blindly agree with the patients. For that reason, this takes up a large toss on the treatment consequences. The orthodontic remedy normally takes up 2-three years for the completion. So this 2 years of treatment will move down the drain given that the retention protocols are accompanied rightly. This is how smart retainers have come into picture. The device is intended to permit a dentist to screen the quantity of time a patient wears his retainer by means of using an electronic device that itself fits into retainer.
Gesture Language Glove

Gesture language recognition is a technology that allows humans and animals to interact with computers and hardware without the need for any mechanical actuation between them.Gestures can include anything from facial expressions, head or eye movements, hand and arm motion, or other bodily movements and can therefore encompass a wide range of control for complicated systems.As sensor technology becomes smaller, cheaper and more readily available, gesture language recognition becomes a more viable solution for projects and systems to employ.This paper presents a prototype gesture language recognition system composed of hobby-grade electronics, compares it against systems using higher-grade hardware or more advanced software algorithms and extrapolates what further technological advancement will do for gesture language recognition systems.
A direct normal irradiation forecasting model based on artificial neural networks

We investigate the forecasting of the hourly Direct Normal Irradiation (DNI) using Artificial Neural Networks (ANN). The data used are hourly satellite data for the region of Ouarzazate in the South West Mediterranean basin region. The database is a total of 19 years. A feed-forward multilayer Perceptron is used with ten input parameters. The results show a very good accuracy for the four seasons of the years forecasted.
A structural attack to the DME-(3,2,q) cryptosystem

We present a structural attack on the DME cryptosystem with parameters (3,2,q). The attack recovers 10 of the 12 coefficients of the first linear map. We also show that, if those 12 coefficients were known, the rest of the private key can be efficiently obtained by solving systems of quadratic equations with just two variables.
Quantum Computing in Data Security: A Critical Assessment

Inception of “quantum supremacy” officially announced by Google has given rise to future threats to data security and privacy. One of the areas that we must focus on is the future threats to all applications dependent on IT, not just restricted to military applications, power distribution, smart cities but all automated infrastructures (especially critical infrastructure). The objective of the study is to make the community aware of the current and future threats to data security and privacy using future quantum applications. The paper mainly demonstrates how PKI and its key exchange method can be compromised easily with the help of quantum computers and also proposes a solution to make our key exchange protocol secured, using QKD which ensures a hackproof exchange of keys between the sender and intended receiver. The paper also explores the research observation areas that can be focused on, for protecting against future threats emerging due to quantum evolution.
Automatic Text Summarization for Code- Mixed Language using Fuzzy Logic

Natural Language Processing (NLP) is a domain of computing and natural linguistics.It is related to the unique conversation among machines and languages used by human.We are leaving in the era of machines, data and intelligence where the amount of information on the Internet is raising continuously, the method which are competent to build it preserved for users, e.g., by text summarization, question answering chat bots etc.The difficulty is highlighted with news stories, where numerous news providers account on same measures by same facts.Application like Automatic text summarization can resolve this challenge.By creating a wide-ranging summary of a given set of documents, Summarization can deal with the problem of information load through retrieving and showing the main content.This is still increased via the escalating quantity of information in community media where collection opinion in diverse languages can be verified.This paper addresses the boundaries of summarization by means of upward techniques that work in an extremely tall quantity and for multilingual scenario.Still the evaluation of automatically formed summaries in diverse languages is a exigent problem for the summarization community, as because human hard work are multiplied to make model summaries for each language.The retention ratio for above method is found to be around 75%.
Polymer nano composites For Water Pollution Applications

Insertion metal particles of nano size in to polymer matrices resulted scientific technical interest. Lot of research work is going on this areas. In the present studies the authors discus various factors effecting the polymer metal nano composites. An attempt has also been made on the work done by the authors. The composites are useful in removal heavy metal ions present in the water.
Desktop and Augmented VR for Delivering Materials for Graphics Modeling and Animation Courses

This paper explains the design of a prototype desktop and augmented Virtual Reality (VR) framework as a medium to deliver instructional materials to the students in an introductory computer animation course.This framework was developed as part of a Teaching Innovation Grant to propose a costeffective and innovative instructional frameworks to engage and stimulate students.Desktop-based virtual reality presents a 3-dimensional (3D) world using the display of a standard desktop computer available in most of the PC labs on campus.This is a required course at this university that has students not only from the primary department, but from other colleges/departments as well.Desktop VR has been chosen as a medium for this study due to the ease-of-access and affordability; this framework can be visualized and accessed with the available computers in PC labs available in university campuses.The proposed research is intended to serve as a low-cost framework that can be accessed by all students.The concepts of 'computer graphics, modeling & animation', instead of being presented using conventional methods such as notes or power point presentations, are presented in an interactive manner on a desktop display.This framework allows the users to interact with the objects on the display not only via the standard mouse and keyboard, but also using multiple forms of HCI such as Touchscreen, Touchpad, and 3D Mouse.Hence, the modules were developed from scratch for access via regular desktop PCs.Such a framework helps effective pedagogical strategies such as active learning (AL) and project-based learning (PBL), which are especially relevant to a highly lab-oriented course such as this course titled 'Introduction to Animation'.Finally, the framework has also been tested on a range of VR media to check its accessibility.On the whole, this proposed framework can be used to not only teach basic modeling and animation concepts such as spatial coordinates, coordinate systems, transformation, and parametric curves, but it is also used to teach basic graphics programming concepts.Hence, instead of a touchscreen, the modules have to be developed from scratch for access via regular desktop PCs.Such a framework helps effective pedagogical strategies such as active learning (AL) and project-based learning (PBL), which are especially relevant to a highly lab-oriented course such as this animation course.
Pemanfaatan Waktu Belajar oleh Pengurus Organisasi Siswa Intra Sekolah (OSIS)

Utilization of study time is important for students. If students cannot use the time to study well this will have a negative impact on their learning outcomes. The reality in the field found that several students who were administrators of the Student Council had not used the time to study well. This is because students are more preoccupied with organizational activities. This study aims to describe the utilization of learning time by the OSIS management which includes 1) making a schedule and its implementation, 2) reading and making notes, 3) repeating the lesson material, 4) concentration and 5) working on the task.The type of research used is descriptive quantitative research. The research subject was the board of student council of SMAN 2 Padang in the 2018/2019 academic year, which was 38 people. The research data was collected using a questionnaire. Data analysis techniques that use percentage techniques.The research findings revealed 1) the utilization of study time by the OSIS administrators in terms of making schedules and their implementation was in a fairly good category, 2) the utilization of study time by the student council administrators in terms of reading and taking notes in a fairly good category, 3) utilization of study time by administrators OSIS in terms of repeating the subject matter is in the fairly good category, 4) the utilization of study time by the OSIS administrators in terms of concentration is in a fairly good category and 5) the utilization of study time by the OSIS administrators in terms of doing assignments is in a fairly good category. Based on the research findings, it can be concluded that the utilization of study time by the Student Council administrators is in a fairly good category.
Intelligent SVD-Based Noise Level Estimation Incorporating Symbiotic Organisms Search

A simple technique for inferring the level of Additive White Gaussian Noise (AWGN) from a still image is presented in this paper. This technique exploits the effectiveness of Singular Value Decomposition (SVD) to estimate the noise level of a noisy image. It investigates the trailing sum of its singular values which contain the noise information of an image. The noise level and two additional parameters own linear dependency with the trailing sum of singular values. The two additional parameters can be experimentally obtained from a given set of noisy images. However, it becomes less satisfied in practical noise level estiation which requires a fast response. Thus, the proposed method utilizes the Symbiotic Organisms Search (SOS) to further optimize the scaling factor, regarded as additional parameter. The extensive experiments show that the proposed method offers a promising result on estimating the noise level. In addition, the estimated noise level can be further employed for the blind image denoising task.
Comparative of ID3 and Naive Bayes in Predictid Indicators of House Worthiness

Decision making is method of solving problems using certain way / techniques so that can be accepted. After making some calculations and considerations through several stages, the decision have taken that decision maker goes through. This stage will be selected until the best decision has made. Decision-making aims to solve problems that solve problems so that decisions with final goals can be implemented properly and effectively. This study uses a simulation of decision making from seven attributes to the proportion of the feasibility of a house based on data from Central Statistics Agency (BPS). There are several techniques for presenting decision making including: ID3 (decision tree) algorithm concept and Naive Bayes algorithm. Both classification are learning-supervised data grouping. ID3 algorithm depicts the relationship in the form of a tree diagram whereas Naive Bayes makes use of probability calculations and statistics. As a result, in data training, decision trees are able to model decision making more accurately. The prediction results using the decision tree model = 90.90%, while Naive Bayes = 72.73%. Meanwhile, the speed of the Naive Bayes algorithm is better
CCTV Intelligent Surveillance on Intruder Detection

With the technology today, the detection of intruders was introduced to decrease theft and crimes.The implementation of this system is made at home.A system with just records of theft would not work, the system should be efficient and faster to detect thefts effortlessly.The goal of this system is to give a new direction of innovation in the closed-circuit television video image processing in computer vision.Having a system to monitor and notify users of potential threats must be implemented, as well as predicting a child's movements at home.Doing this in real-time ensures a lot of human labor to be minimized while also ensuring recognition using computer vision.This document provides an outline of the intrusion detection system and danger prevention system for children outside and inside the home environment, with the help of image processing, face recognition, and training of the model through machine learning.For an instance, if a kid at home reached near the well in the garden area, system predicts whether the kid is reaching the well by deriving it from the distance calculated earlier and sends an alert to the mobile or any device where an application is installed.Same prediction applies for any intruders to reach the home or any restricted places at home.
Artificial Intelligence a Driver for Digital Transformation

Artificial intelligence is reconfiguring the economy and redefining the product and service market. It is a disruptive technology that leads to the creation of multiple more efficient activities, new business models, and industrial processes. The literature stresses that AI should be used in all aspects of the personal lives of organisations and individuals, and such complexities are still largely unstudied. The aim of this study is to highlight AI's innovations and applications to the organisation's digital transformation.
Software for automated reading of sunshine duration by Digital Image Processing

The present study aims to demonstrate the benefits and results obtained from software for filtering, processing and managing sunshine duration monitored by heliographs, in meteorological stations. The source code of the software was developed using the Java EE 7 (Java Enterprise Edition) programming language, based on internet applications. Information storage and management was performed by the MySQL 5.7 Database Management System (DBMS). Digital image processing techniques, incorporated in the software, allowed to count sunshine duration in an automated and standardized way, eliminating errors due to the complexity and subjectivity in the measurement observation, performed manually. Processing routines were implemented to apply filters in the spatial domain, enhancing digital images of sunshine data, to better identify parts of interest and ensure quality in the accounting process. For software validation, a set of September 2015 sunshine data, provided by the Lageado Meteorological Station of the School of Agricultural Sciences (UNESP) of Botucatu - SP, was used. In which, comparisons between readings performed by the computer program and readings performed manually showed MBE values of 0.130 hours (rMBE = 1.908%), RMSE of 0.259 hours (rRMSE = 3.791%) and R of 0.998. Indicating that the software can be used to read sunshine data, as it ensures automation, standardization and speed in the process.
Sentiment Analysis On Twitter Using The Target-Dependent Approach And The Support Vector Machine (SVM) Method: Sentiment Analysis On Twitter Using The Target-Dependent Approach And The Support Vector Machine (SVM) Method

Opinions or sentiments given by the public on Twitter social media have attracted attention for research. In this study, what will be done in connection with sentiment analysis on Twitter is to use a target-dependent approach. Where given a data twit or opinion relating to 3 major cities in Indonesia, namely Jakarta, Bandung and Medan, and will be classified as opinions that are positive, negative or neutral. Due to the social media used is Twitter, which can only write opinions in 140 characters, it is possible to find data on tweets or ambiguous opinions. Therefore, this study focuses on sentiment analysis with a target-dependent approach using the SVM method for classification. The target-dependent approach itself consists of 2 stages, namely determining matters relating to the topic of discussion and collecting data on tweets related to the topic. Broadly speaking, this research was carried out in 4 stages, namely preprocessing, classification with a target-dependent approach and SVM method and finally the determination of opinion classification)
A Primer for Blockchain

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On Data-Augmentation and Consistency-Based Semi-Supervised Learning

Recently proposed consistency-based Semi-Supervised Learning (SSL) methods such as the Pi-model, temporal ensembling, the mean teacher, or the virtual adversarial training, achieve the state of the art results in several SSL tasks. These methods can typically reach performances that are comparable to their fully supervised counterparts while using only a fraction of labelled examples. Despite these methodological advances, the understanding of these methods is still relatively limited. To make progress, we analyse (variations of) the Pi-model in settings where analytically tractable results can be obtained. We establish links with Manifold Tangent Classifiers and demonstrate that the quality of the perturbations is key to obtaining reasonable SSL performances. Furthermore, we propose a simple extension of the Hidden Manifold Model that naturally incorporates data-augmentation schemes and offers a tractable framework for understanding SSL methods.