Reviewerly/exHarmony huggingface dataset:
Framework for Processing Medical Data and Secure Machine Learning in Internet of Medical Things

The term «Internet of Medical Things» (IoMT) refers to a set of devices and technologies for remote monitoring of patients’ health using wearable devices. One primary problem with patient’s data is ensuring privacy when it is transmitted over open communication channels and stored in cloud systems. A whole range of different approaches to these issues are available. However, when it comes to millions of IoT devices, technologies that have already become classic for Internet resources are not suitable in many aspects at once. The aim of this work is to develop methods and protocols for secure interaction between portable diagnostic devices and cloud services for the analysis and processing of medical data in the Internet of Medical Things networks. The work considered existing technologies and solutions for ensuring security in IoMT networks and personalized medicine systems; also, it focused on secure machine learning methods. Previous studies have emphasized attribute-based encryption (ABE) as a prospective method for data privacy and security. These algorithms solve many problems for IoMT applications: patient’s data confidentiality, flexible key management, fine-grained access control mechanisms, and user control over data. We have proposed a framework for processing patient data from portable diagnostic devices using ABE methods.
LibGuides: Research & Writing Skills: Writing Help

A guide designed to help you with research! This includes finding a topic, researching your topic, evaluating information, using APA, writing skills, and all kind of helpful things! Resources centering on helping you become a better writer!
Application of The Naive Bayes Classifier Method In The Sentiment Analysis of Twitter User About The Capital City Relocation

Abstract. The president's official decision regarding the relocation of the capital city, which previously was in Jakarta and will be moved to East Kalimantan, will be a big issue and generate a lot of debate from both the agree and the disagree Indonesian citizen because this project will require a lot of funds and will have massive impacts on various sectors. This study uses 1290 tweet data consisting of 686 negative sentiments and 603 positive sentiments. These data were used as training data to create evaluation models using confusion matrix and split validation techniques. In this study, it is used TF-IDF word-weighted feature extraction with the Naive Bayes method. The result from the experiments, which was carried out on the best accuracy by splitting data 90:10 for training and testing respectively, is 76.74%. The model that has been made is implemented in 1115 test data resulting in 799 negative sentiments and 316 positive sentiments.
LibGuides: Research Starter - COMM 499: Determining the Reliability of a Resource

This page will help explain the difference between Primary and Secondary sources. You will also learn how to determine the reliability of a resource and/or website
Guiding Principles for Updating the Product Liability Directive for the Digital Age (Pilot ELI Innovation Paper)

An ELI Innovation Paper seeks to set out concrete propositions for European Legal Development in a short paper, which is more tentative in nature and which does not represent the result of comprehensive research; rather, it seeks to spark discussion and to inspire further action. In this spirit, this Pilot Innovation Paper proposes a set of ‘Guiding Principles’ to prompt further discussion both in terms of detail and of how these Principles could lead to reform of the European Union’s Product Liability Directive. It suggests that such reforms could be structured around 10 'Guiding Principles'
Fashioning research student’s competence of engineering higher schools in the process of independent and scientific research

The surveyed problem is relevant today because of the existing discrepancy between the increased need of the society and the government in high quality university engineering education and the real maturity of engineering graduates to perform their professional duties, as well as the insufficiently developed theoretical foundations of student research in the context of competence-oriented education. The purpose of this paper is to solve the problem of forming the research competence of students in the course of independent and scientific research work in the educational process at University of engineering. Based on the systematization and development of existing approaches to the solution of the problem of research training for engineering university students contributing to the development of a functional model, a methodology for the formation of research competence in the course of independent and scientific research work of students of engineering universities is presented. The viability and expediency of creation and work of initiative groups focused on the fulfillment of creative research assignments is substantiated. The process of fashioning practical experience of research activity with the participation of students in scientific seminars is described; the process of using projects method through research tasks in the implementation of coursework, qualification works is presented; fixing and improving the experience of research activities of future engineers during all types of practice is considered.
Generalized Net Model for Flying Ant Colony Optimization

Ant Colony Optimization (ACO) has been used successfully to solve hard combinatorial optimization problems. The method is inspired by the foraging behavior of real ant colonies, which manage to establish the shortest routes to feeding sources and back. In ACO the problem is represented as a graph and our artificial ants look for a shorter path taking in to account some constraints. The method is constructive. Every ant creates its solution, starting from random node. It includes new node in the partial solution according probabilistic rule. In traditional ACO an ant can observe only the neighbor nodes and decides to include it or not in the partial solution. In our previous work we propose ACO with flying ants. The ants make a decision regarding more than one step forward, they observe the neighbors of the neighbors too. Thus they can make better decision. The Generalized Nets (GN) is a powerful tool for modeling real processes. In this work we apply GN for modeling Flying Ant Colony Optimization (FACO). Description of FACO by GN can give us new ideas for further development and improvement of the algorithm.
Review Paper: Face Recognition Techniques in Digital Image Processing

Purpose: This paper aims to explore the face recognition process, the accuracy of the face recognition system, and the system can recognize face in real time. Background: Face recognition is a biometric technique that allows a computer to recognize faces by comparing the input image with the image from the provided database. Currently, face recognition has been widely used in various fields and one of these usages is for security systems. In a security system, a high accuracy and very good performance in the face recognition process is needed. Design/Methodology/Approach: . There are many methods used in face recognition systems, some of them are Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Nearest Neighbor, Gabor Wavelet and Boosted Cascade Classifier. There are several factors that influence the success of the face recognition system, namely the distance of the face to the device such as camera, lighting, the number of images of people's faces stored and the performance of the computer used. Results/Findings: The accuracy and performance values from the PCA, LDA, K-Nearest Neighbor, Gabor Wavelet, Boosted Cascade Classifier method with several test samples according to the factors that influence success in the face recognition system will be exposed. Conclusion and Implications: This paper is expected to make readers who want to build systems with face recognition features easier to determine which method will produce the appropriate level of accuracy without reducing the performance of the system built.
Approximate Coalgebra Homomorphisms and Approximate Solutions

Terminal coalgebras $$\nu F$$ of finitary endofunctors F on categories called strongly lfp are proved to carry a canonical ultrametric on their underlying sets. The subspace formed by the initial algebra $$\mu F$$ has the property that for every coalgebra A we obtain its unique homomorphism into $$\nu F$$ as a limit of a Cauchy sequence of morphisms into $$\mu F$$ called approximate homomorphisms. The concept of a strongly lfp category includes categories of sets, posets, vector spaces, boolean algebras, and many others. For the free completely iterative algebra $$\varPsi B$$ on a pointed object B we analogously present a canonical ultrametric on its underlying set. The subspace formed by the free algebra $$\varPhi B$$ on B has the property that for every recursive equation in $$\varPsi B$$ we obtain the unique solution as a limit of a Cauchy sequence of morphisms into $$\varPhi B$$ called approximate solutions. A completely analogous result holds for the free iterative algebra RB on B.
An Analytical Framework Considering the Effects of Online Teaching Quality on Student Satisfaction

COVID-19 spreads across the world in late 2019 has affected to several aspects of social life.One of the most important sectors, which face difficulties was education, thus most universities have transferred from traditional education to online education through the internet to make their academic year going.This study aims to review the effects of online teaching quality on student satisfaction, a positive attitude resulting from an evaluation of students' online teaching experience in higher education.Through applying the SERVQUAL model to measure the effects of online teaching quality on students' satisfaction, it can be expected to get better the online teaching quality of higher education institutions in Vietnam.
SISTEM PAKAR DIAGNOSIS PERUBAHAN CUACA BERBASIS ANDROID

Weather is part of carrying out an activity and affects several fields, such as determining crops in agriculture and aviation on departure in an airplane. Android is an operating system that can be used and is open source code, android can develop and modify easily. The Meteorogy, Climatology and Geophysics Agency (BMKG) is tasked with monitoring the weather that predicts the weather using two methods, namely conventional methods and statistical methods which can cover a radius of 5-10 km on land and 50 km at sea for observations in a predicted area. The problem in this study is that the weather diagnosis requires a complex database, so a method for accurate weather diagnosis is needed and weather diagnosis information is very difficult to obtain. Forward chaining is a technique that starts the search for data and facts, and the data is used as a conclusion to become a solution. So the forward chaining method can help make diagnoses related to the weather. The purpose of diagnosing weather changes is to be able to help the special community in the Riau Islands to help plan activities. Researchers are designed to be able to assist the surrounding community in obtaining weather diagnosis information by providing complete information and accurate results but carried out efficiently. Keywords: Weather, Android, Forward Chaining, BMKG
Approximation spaces of deep neural networks

We study the expressivity of sparsely connected deep networks. Measuring a network's complexity by its number of connections, or its number of neurons, we consider the class of functions which error of best approximation with networks of a given complexity decays at a certain rate. Using classical approximation theory, we show that this class can be endowed with a norm that makes it a nice function space, called approximation space. We establish that the presence of certain skip connections has no impact of the approximation space, and discuss the role of the network's nonlinearity (also known as activation function) on the resulting spaces, as well as the benefits of depth. For the popular ReLU nonlinearity (as well as its powers), we relate the newly identified spaces to classical Besov spaces, which have a long history associated to sparse wavelet decompositions. The established embeddings highlight that some functions of very low Besov smoothness can nevertheless be well approximated by neural networks, if these networks are sufficiently deep.
ANALISA SISTEM KOMUNIKASI DATA PADA SIMULASI ROBOT SEPAK BOLA BERODA

Internet network can connect every computer that is connected in it, not only sharing information but also enables each computer to do work together, thus allowing users to control other computers. In football robot requires good coordination between robots using decision making or control carried out by one robot that requires data on the environmental conditions of all robots. Therefore we need a reliable data communication system. This research aims to design and analyze a data communication system on a soccer robot team. The method used in this research is to build a communication system between clients and servers using the secure shell (ssh) protocol. The secure shell (ssh) protocol is a network protocol located at the application layer of the TCP / IP protocol, which is used to control computers (remotely), send files, and others. This secure shell (ssh) protocol is used to connect clients and servers to robot simulations using the Robot Operating System (ROS) software as a tool to make robot software and Gazebo software as simulators. The quality of the data communication that was designed was then tested using Wireshark software. The parameters of Quality of Service will be measured between throughput, delay, packet loss, and jitter that refers to the TIPHON standard. Based on the results of testing the data communication system that has been done by placing the machine close to the access point, the average throughput is 28,02619 kbps (very good), an average packet loss of 0% (very good), a delay of 0.28651552697192 ms (very good ), and jitter for 0.00000814 ms (good). Meanwhile testing by placing the machine within 10 meters with an access point obtained an average throughput of 15,44595 kbps (very good), an average packet loss of 0% (very good), a delay of 0.520748991128 ms (very good), and jitter of 0.0000144 ms (good). From the tests conducted showed that the communication system that was made was by the initial plan and the communication system was reliable.
Implementación de un laboratorio de cómputo con software y hardware libres

Objetives: To implement a low cost computer laboratory, using free hardware such as Raspberry PI and free software such as Linux, for the support of primary schools that do not have the economic capacity to solve the purchase of a conventional computer laboratory, in order to increase the interest of students from first to 6th grade of the use of ICT in daily life. Methodology: An analysis of the different existing linux distributions for the raspberry PI was carried out, as well as the different free software programs that would be used in the classrooms, such as mathematics, history, reading, science and programming principles. Contribution: The use of free software tools in the classroom, is not only a matter of economy, but also the teaching of the 4 freedoms of free software, use, share, distribute, and the possibility of improving it knowing the source code. It also promotes collaborative work, and the use of free hardware has the advantage of technological independence.
Causality in Time Series Systems

Causality inference for time series systems has been subject to intensive researchacross many generations of physicist and, in light of the boom of computationalresources, has been increasingly applied to a wider range of areas such as biologyor finance. In this thesis we structurally compare three inference methods, GrangerCausality, Transfer Entropy, and Convergent Cross Mapping, by applying them tosynthetic nonlinear systems. While we verify that Granger Causality only detectslinear causal relations, our analysis with Fourier Transform surrogates shows thata significant amount of causality, measured by Transfer Entropy and ConvergentCross Mapping, is driven by nonlinear properties. Our study of the Lorenz attractorfurther suggests different structures for different timeframe lengths. Upon introducingmeasures for the system causality, we observe that the long-term causality of thesystem remains approximately constant with a major nonlinear component. Ona short-term scale, the causality resolution changes, which we can map to certainlocations within the attractor. We find these properties to apply to several othersynthetic nonlinear systems. The resulting framework is designed to be applicable toreal-world time series systems in order to detect unknown causality structures anddrivers in other research areas.
Export of Educational Services from a Border Region

Current strategic development goal of Russian education is to increase its competitiveness through integration into the international educational and scientific community. The article aims to consider a set of issues related to the study of trends and prospects of cross-border cooperationâ€™s development between Russia and Kazakhstan in the sphere of education. As a research methodology we used system and functional approaches, economic and statistical methods, which allow identifying the features of cross-border cooperation in the field of education exports at the regional level. Besides analyzing the status of such cooperation between Russia and Kazakhstan, we performed a research on foreign citizens who study in Russian universities. Therefore we revealed the main directions of cooperation between the Orenburg region and Kazakhstan in the context of the regions leading universities: network interaction, export of educational and scientific services, international academic exchanges, training programs. Particularly, we focused on indicators of foreign Kazakhstan studentsâ€™ training. They include changes in the pupils number, the most popular education programs, and sources of funding. We have concluded that it was necessary to create a concept for the development of education exports in the context of cross-border cooperation. These findings can be used for developing comprehensive measures and introducing new approaches to the use of universitiesâ€™ potential and resources in the border region and Kazakhstan for achieving maximum results in all areas of cooperation.
Copyright and Creative Artificial Intelligence (AI) Systems: A Twenty-First Century Approach to Authorship of AI-Generated Works in the United States

This note is divided into five sections. The first section provides a brief definition, preliminary history, and summary of the latest developments of Al technology. This is followed by an in-depth investigation into the copyrightability of Al-generated works in the second section. Importantly, the second section will trace the locus of difference between human creativity and computational creativity and propose policy changes in the application of the notion of the originality which serves as a requisite for the allocation of authorship for copyright purposes. The third section will explore reasons to accept Al-generated works as copyrightable based on utilitarian grounds. Having thus established the grounds of copyright protection eligibility for Algenerated works, the fourth section will determine how authorship of these works is best attributed or recognized through a comprehensive analysis of the merits of seven plausible options: (i) the Al system itself as author; (ii) the programmer as author; (iii) the trainer as author; (iv) the user as author; (v) joint authorship; (vi) public domain or; (vii) the data proprietor. The final section proposes a solution to who should be accepted as the author of Al-generated works that better serves constitutional purposes and balances the many interests that are likely to arise between the various actors who develop creative machines or who lawfully obtain such machines.
Android App for Store Management System

The store management system makes an application structure that improve a store of school and industry to design its collecting exercises reliant on the step-by-step update of arrangements from its users. Exactly when the publicizing projections of things as far back as week are entered by the merchants over the web nearby the orders for the going with convenience, the arrangement for the following week’s creation will be drawn up. A report of the fundamental rough materials or products and things will be drawn up with the thing requirements over the web and mentioned to refer to their rates. At the point when the rates are referred to, the transport will be set with the essential movement plans. At the point when the things are given the stocks will be invigorated. By then a creation plan will be drawn up taking the bill of stocks into thought. At the point when the creation plan is embraced, the stock will be invigorated when the thing is given. At the point when the finished things are free the transport schedules will be drawn up subject to the orders set by the dealers. The materials with the merchants will moreover be kept up. Stock management and stock report is the system which is widely used in the industry or college. Therefore, only by establishing a shared stock management system for the various departments of the enterprise enabled enterprises to timely and effective control of its own stock of resources, management and rational use. The system will be fully generalized and have control on Stock Management, Expenditure, Reports, Sales, Delivery, Purchase with a centralized connectivity to the database. The system is also accessible on the mobile, hence, it makes the usage of the system more easily to the stock manager.
A Hierarchical Approach for Joint Extraction of Entities and Relations

Most existing approaches for the extraction of entities and relations face two main challenges: extracting overlapping relations and capturing the interactions between entity and relation extractions. In this paper, we present a novel sequence-to-sequence model with a hierarchical decoder to solve both issues elegantly and efficiently. Specifically, we use the low-level decoder to predict multi-relations and produce a relation vector for each triple. Given this relation vector, the high-level decoder generates two entities associated with the triple. In this manner, we can directly capture the interactions between entity and relation extractions. Moreover, by decomposing two tasks into two decoding phases, the overlapping multi-relations extraction can be naturally separated. Experiments on popular public datasets demonstrate that our model can effectively extract overlapping triples.