Reviewerly/exHarmony huggingface dataset:
PCN308 Natural Language Processing to Understand the Landscape of Patient-Reported Outcomes in a Specific Disease Area

Understanding how Patient-Reported Outcomes (PROs) have been utilized in previous studies is important for Clinical Trial design, but also challenging as it can require reading thousands of articles to identify specific instruments and relevant symptoms. We present an artificial intelligence (AI) algorithm to search within PubMed to generate a set of disease-specific insights and symptoms, tying these to PRO measures where relevant. The goal is to uncover the instruments used in the literature, and the domains those instruments measure. To start, we use AI to surface nearly 125,000 clinical-outcome results from 18,000 papers related to Head and Neck Squamous Cell Carcinoma. Some results were PROs or target, and some were off target, such as survival rates or adverse events. Our algorithm then filtered these clinical outcomes to those that contained generic PRO terms, such as “index” or “scale.” This yielded 2,528 potential outcomes more aligned with PROs. However, these still contain non-PRO measures, such as “tumor index value.” Next, our algorithm identified the most commonly occurring nouns/noun-phrases within the filtered set of 2,528 outcomes, surfacing the more prominent PRO themes. We then picked out the key terms such as “voice” or “quality of life” as separate themes. Some of these themes are specific PRO instruments and some are symptom scales. For instance, the “quality of life” theme includes the “EORTC quality of life questionnaire,” while “voice” includes “voice handicap index.” This approach identified 47 themes, associated with 441 papers. The whole process, from initial data curation to PRO identification, took less than 30 minutes. The algorithm presented here allowed us to understand which patient-centric themes and symptoms are important, and gather how previous trials used PROs. Further, it has the potential to be more thorough and insightful than a standard literature review.
VISUALIZATION OF E-COMMERCE DATA USING AUGMENTED REALITY

Data visualization is viewed as a significant element in data analysis and communication. As the data engagement becomes more and more complex, visual presentation of data does help users understand the data. So far, two-dimensional (2D) data visuals are often used for the data visualization process, but the lack of depth dimension leads to inefficient and limited understanding of the data. Therefore, the effectiveness of augmented reality (AR) in data visualization was studied through the development of an AR Data Visualization application using E-commerce data. Machine learning models are also involved in the development of this AR application for the provision of data using predictive analysis functions. To provide quality E-commerce data and an optimal machine learning model, the data science process is carried out using the python programming language. The E-commerce data selected for this study is open data taken through the Kaggle Website. This database has 9994 data numbers and 21 attributes. This AR data visualization application will make it easier for users to understand the E-commerce data in-depth through the use of AR technology and be able to visualize the forecasts for sales profit based on the algorithm model "Auto-Regressive Integrated Moving Average" (ARIMA).
Development of internet psychology in Ukraine and in the world

The article is devoted to a new branch of psychological science that is the Internet psychology. The current state of the psychology of the Internet, some prerequisites for its development, main directions, achievements and unresolved problems are analyzed. The purpose of the research is to analyze of the current state of Internet psychology, outline the prerequisites for its development, main directions, achievements and unresolved problems. For this purpose, methods and techniques of generalization, analysis and synthesis were used to prepare the theoretical part, also elements of conceptual analysis (definition of meaningful structure, isolation of keywords) were used to classification of the mentioned studies. The author comes to the conclusion from the theoretical analysis that the Internet psychology in the meaning of a branch of psychology unites the methodology, theory and researching practice of the types, methods and principles of people using of Internet services. It appeared almost immediately after the Internet and develops in parallel with it. Now this branch is still at the stage of formation and requires significant revision of the terminological apparatus and the development of its own methodological base. Her active development will depend directly of increasing amount of time that modern man spends in cyberspace. In addition, the article identifies some significant discoveries in the area of the Internet psychology, classic works, main research problems and their representatives, and also the technical and psychological specifics of the Internet in their interconnection. The key directions of the modern Internet psychology developing are the psychological analysis of human-internet interaction, the psycholinguistic specificity of Internet genres and discourses, the peculiarities of Internet communication, the specificity of virtual world existence (psychology of hypertext), personality on the Internet. The technical specificity of virtual technology causes some psychological features on the Internet, in particular the restriction of sensory experience only visual and auditory, different from the real world sense of space and time, the emergence of negative emotions with limited accessibility to cyberspace, the constant fixation of cyberspace results, virtual identity, online self disengagement, status alignment, unlimited contact availability, changing priorities.
SYSTEM-ACTING APPROACH FOR DEVELOPMENT OF MATHEMATICAL COMPETENCIES RELATED TO THE VALUE ”MASS” IN THE EDUCATION IN MATHEMATICS FOR GRADES 1-4

The development of knowledge, skills and competences related to values and their measuring units represents an important part of the overall education in mathematics for primary school students in Grades 1-4. The research studies different theoretical concepts related to the competences and the approaches in the primary school education. Based on the analysis of the respective legislation the researcher presents interconnections between the specific mathematical competences and the term “mass” from the competency cluster “Measurement”. The newly developed methodology system of work for learning the term “Mass” is applied during both the mandatory and the additional mathematics classes in Grades 1-4. Different approaches for education are simultaneously applied but priority is given to the system-acting approach with the idea to achieve unification between the act of teaching and the control of the cognitive and practical productive activities of the students. As a result of applying the newly developed methodology system of work the students actively participate in the pedagogy interrelations and co-operation with the rest of the students, they have the opportunity to express their own intellectual and emotional potential. When the students make mistakes, during the practical individual, team and group activities they get the opportunity to correct these mistakes and to develop their own logical thinking.
How to Get a Degree-Anonymous Graph Using Minimum Number of Edge Rotations

A graph is k-degree-anonymous if for each vertex there are at least $$k-1 $$ other vertices of the same degree in the graph. Min Anonymous-Edge-Rotation asks for a given graph G and a positive integer k to find a minimum number of edge rotations that transform G into a k-degree-anonymous graph. In this paper, we establish sufficient conditions for an input graph and k ensuring that a solution for the problem exists. We also prove that the Min Anonymous-Edge-Rotation problem is NP-hard even for $$k=n/3$$ , where n is the order of a graph. On the positive side, we argue that under some constraints on the number of edges in a graph and k, Min Anonymous-Edge-Rotation is polynomial-time 2-approximable. Moreover, we show that the problem is solvable in polynomial time for any graph when $$k=n$$ and for trees when $$k=\theta (n)$$ .
Hybrid Chaotic Method for Medical Images Ciphering

Healthcare is an essential application of e-services, where for diagnostic testing, medical imaging acquiring, processing, analysis, storage, and protection are used. Image ciphering during storage and transmission over the networks used has seen implemented using many types of ciphering algorithms for security purpose. Current cyphering algorithms are classified into two types: traditional classical cryptography using standard algorithms (DES, AES, IDEA, RC5, RSA, ...) and chaos cryptography using continuous (Chau, Rossler, Lorenz, ...) or discreet (Logistics, Henon, ...) algorithms. The traditional algorithms have struggled to combat image data as compared to regular textual data. Whereas, the chaotic algorithms are more efficient for image ciphering. The Significance characteristics of chaos are its extreme sensitivity to initial conditions and algorithm parameters. In this paper, medical image security based on hybrid/mixed chaotic algorithms is proposed. The proposed method is implemented using MATLAB. Where the image of the Retina of the Eye to detect Blood Vessels is ciphered. The Pseudo-Random Numbers Generators (PRNGs) from the different chaotic algorithms are implemented, and their statistical properties are evaluated using the National Institute of Standards and Technology NIST and other statistical test-suits. Then, these algorithms are used to secure the data, where the statistical properties of the cipher-text are also tested. We propose two PRNGs to increase the complexity of the PRNGs and to allow many of the NIST statistical tests to be passed: one based on two-hybrid mixed chaotic logistic maps and one based on two-hybrid mixed chaotic Henon maps, where each chaotic algorithm runs side-by-side and starts with random initial conditions and parameters (encryption keys). The resulting hybrid PRNGs passed many of the NIST statistical test suits.
Convergence Rates for Multi-classs Logistic Regression Near Minimum.

In the current paper we provide constructive estimation of the convergence rate for training a known class of neural networks: the multi-class logistic regression. Despite several decades of successful use, our rigorous results appear new, reflective of the gap between practice and theory of machine learning. Training a neural network is typically done via variations of the gradient descent method. If a minimum of the loss function exists and gradient descent is used as the training method, we provide an expression that relates learning rate to the rate of convergence to the minimum. The method involves an estimate of the condition number of the Hessian of the loss function. We also discuss the existence of a minimum, as it is not automatic that a minimum exists. One method of ensuring convergence is by assigning positive probabiity to every class in the training dataset.
Combatting the data volume issue in digital forensics : A structured literature review

The increase in data volume and amount of data sources submitted as evidence such as from Internet of Things (IoT) devices or cloud computing systems has caused the digital forensics process to tak ...
Multi Scale Temporal Graph Networks For Skeleton-based Action Recognition

Graph convolutional networks (GCNs) can effectively capture the features of related nodes and improve the performance of the model. More attention is paid to employing GCN in Skeleton-Based action recognition. But existing methods based on GCNs have two problems. First, the consistency of temporal and spatial features is ignored for extracting features node by node and frame by frame. To obtain spatiotemporal features simultaneously, we design a generic representation of skeleton sequences for action recognition and propose a novel model called Temporal Graph Networks (TGN). Secondly, the adjacency matrix of the graph describing the relation of joints is mostly dependent on the physical connection between joints. To appropriately describe the relations between joints in the skeleton graph, we propose a multi-scale graph strategy, adopting a full-scale graph, part-scale graph, and core-scale graph to capture the local features of each joint and the contour features of important joints. Experiments were carried out on two large datasets and results show that TGN with our graph strategy outperforms state-of-the-art methods.
Syntactical Error Analysis on Conjunctional Students’ English Narrative Composition

&lt;p class="8Abstractcontent"&gt;The aims of this research are to know the errors made by the learners on their English narrative composition; to identify the factors made the errors by learners; to identify the errors made by the learners; to correct the errors which have been made; to improve the teaching quality appropriating the curriculum and the syllabus; as well as to get the data and the explanation about the difficulties in studying English especially in arranging the conjunction of English narrative composition. The method used in this research is descriptive method that gives the data and the explanation about the recent symptoms of the errors made by the learners. The descriptive method consists of the ways in giving the note, the analysis and the interpretation about the recent condition. The characteristic of the descriptive method is to give the existence of the data which is straight to the problems as the recent variables are not manipulated. The research was carried out by conducting a written test of English narrative composition for the learners. After analyzing the data, the findings point out that the errors of coordinate conjunction are 33.3% and the subordinate conjunction is 66,7 %.&lt;/p&gt;&lt;p&gt; &lt;/p&gt;&lt;strong&gt;Keywords:&lt;/strong&gt; syntactical error, conjunctional, narrative text
Sistem Pakar Diagnosa Kerusakan VGA dengan Metode Certainty Factor dan Algoritma K-Nearest Neighbor (K-NN)

VGA (Video Graphics Array) is a Video adapter which is very useful for improving the performance and quality of the visual process on a computer, but sometimes there is often a malfunction that cannot be identified the type of damage. The problem is the lack of media to identify the damage that occurs during visual processing. Therefore, the authors created an expert system that can diagnose the type of damage to VGA using the Certainty Factor method as a calculation, using UML modeling as the work process flow of the system on the website, and also equipped with the KNN (K-Nearest Neighbor) algorithm as machine learning. so that it can build an expert system with the PHP programming language MySQL database. The method used in testing is the black box method in testing the system used. The results that can be concluded from this study are; 1) The diagnostic system for detecting damage to the VGA uses the K-Nearest Neighbor Algorithm as machine learning and the Certainty Factor Method as a calculation medium in determining the distance from the type of damage and has suggestions for further actions to deal with and prevent the damage from occurring and also has other possible damage things that are similar to the damage suffered can be accessed quickly and easily to understand, in making scientific research carried out sequentially to facilitate the process, and 2) In addition to diagnosing, there are several additional menus that can be accessed such as the Prediction menu which functions to displays the max and min limits of the temperature of a product, Product Info which functions as a quality product recommendation, and a description that contains a post of details of the damage that can be studied and is expected to help users find solutions to their problems.Keywords:Expert System, PHP, Certainty Factors, Machine learning, K-NN.
Approaches to assessing the semantic similarity and future citation of publications by identifying informative terms with predictive properties

The article discusses new approaches to assessing the semantic similarity of documents in a vector space, taking into account statistically significant and informative terms. Informative terms reflect the current state of research in a certain field of research. To select informative terms, an algorithm for calculating the impact factor of the term is proposed. It is shown that informative terms allow both to evaluate the semantic similarity of texts and to predict future citations. The developed methods for assessing the semantic similarity and future impact of scientific publications can be used in the framework of “Predictive optimization”, a modern technology that allows us to make decisions based on forecasts. In evaluating the activities of research and individual scientists, bibliometric indicators often play an important role. However, the use of citation-based indicators is problematic in determining the impact of recent publications. Usually, two years after the publication of most articles, they receive only a few links. The probability of future citation can be predicted using the proposed indicator - IFT.
The development of creative competence of primary school students under the condition of inclusive education

The importance of formation and development of creativity of primary school students is recognized by specialists in pedagogy and psychology. At the same time, one of the topical problems is the increase in the number of children with special educational needs. The purpose of the study is to regard the function of the aesthetic and imaginative perception of the world as a constituent of creative competence of primary school students in the context of a potential growth point for a child with specific learning disabilities. The subject of the study is the dynamics of indicators of creative competence (creative imagination, in particular) demonstrated by children as a result of mastering an integrated set of activities aimed to develop creative thinking in primary school students to be able to solve tasks, as well as to form creative competence, to improve self-expression and self-regulation through the use of tools of creative activities and to introduce children to works of culture and art in the conditions of inclusive education. At the stage of the ascertaining experiment, the creative imagination of children participating in the experiment was evaluated according to the methodologies of Dyachenko O. ("Drawing figures") and Kravtsova E. ("Where is its place?"). The general tendency, which is true for the results of the ascertaining experiment with the application of both methods, is the absence of children with a high level of imagination development in the group studied. Integrated lessons aimed to the formation and development of creative imagination in children with developmental delay were carried out for a year and a half, in inclusive groups. In the course of the complex work, the elements of art therapy, logopedic rhythm, psycho-gymnastics, fairy-tale therapy, dance movement therapy and music therapy were used, the means of theatricalization and dramatization were actively applied. According to the results of the ascertaining experiment, it is revealed that the subjects have the ability to overcome the stereotypes formed on the basis of the accumulated experience, which is one of the elements that determine the success of creative activity. As a result of the study, it was discovered that creative imagination regarded as a component of the creative competence of primary school students could be stimulated and improved with the help of a psychological-pedagogical influence during the application of the methodology of integrated lessons of the aesthetic course.
О взаимном расположении мегалитических комплексов Гунунг-Паданг и Мачу-Пикчу

The unusual relative locations of the megalithic complexes Gunung Padang on Java in Indonesia and Machu Picchu in Peru, unveiled with the help of Digital Earth, both located on opposite sides of Earth – on the meridians spaced from each other by 180 degrees – is considered in the work. The possibility and methodology of using Digital Earth in the search and interpretation of hypothetical hyper structures of archaeological sites is discussed.
Building Graphs at a Large Scale: Union Find Shuffle.

Large scale graph processing using distributed computing frameworks is becoming pervasive and efficient in the industry. In this work, we present a highly scalable and configurable distributed algorithm for building connected components, called Union Find Shuffle (UFS) with Path Compression. The scale and complexity of the algorithm are a function of the number of partitions into which the data is initially partitioned, and the size of the connected components. We discuss the complexity and the benchmarks compared to similar approaches. We also present current benchmarks of our production system, running on commodity out-of-the-box cloud Hadoop infrastructure, where the algorithm was deployed over a year ago, scaled to around 75 Billion nodes and 60 Billions linkages (and growing). We highlight the key aspects of our algorithm which enable seamless scaling and performance even in the presence of skewed data with large connected components in the size of 10 Billion nodes each.
Första mötet med e-boken : Intervjuer med vuxna läsare

This bachelors thesis explored first time reader's reactions to e-books. Focusing on how the new readers relationship to the printed book influenced their reading experience. Eight qualitative semi ...
Survei Pasar Perancangan Produk pada Alat Finger Spalk di Klinik Fisioterapi Anugrah Sehat menggunakan Kuesioner

Mallet finger adalah kondisi cedera pada tendon jari yang mengakibatkan ujung jari tangan tidak bisa bergerak lurus dan membutuhkan bantuan untuk meluruskannya. Survei merupakan alternatif metode komunikasi dengan mengajukan pertanyaan pada responden dan merekam jawabannya untuk dianalisis lebih lanjut. Permasalahan dalam teknik survei lebih terkait dengan pembuatan kuesionernya karena berhubungan langsung dengan daya tanggap responden. Pengambilan data yang dilakukan adalah dengan metode sampling, dimana pengumpulan data yang hanya mengambil sebagian elemen populasi atau karateristik yang ada dalam populasi. Dan metode sampling yang digunakan adalah metode probability sampling dengan teknik sampling yaitu simple random sampling yaitu cara pengambilan sampel dengan semua objek atau elemen populasi memiliki kesempatan yang sama untuk dipilih sebagai sampel. Kuesioner merupakan sejumlah pertanyaan tertulis yang digunakan untuk memperoleh informasi dari responden dalam arti laporan tentang pribadinya, atau hal-hal yang ia ketahui. Kuisioner yang digunakan yaitu kuesioner terbuka dan kuisioner tertutup. Mallet finger is a condition of injury to the finger tendon that results in the tip of the finger not being able to move straight and needs help to straighten it. Surveys are an alternative method of communication by asking questions to respondents and recording their answers for further analysis. Problems in the survey technique are more related to making the questionnaire because it is directly related to respondent responsiveness. Data retrieval is done by sampling method, where data collection that only takes a portion of the population or characteristics of the population. And the sampling method used is the probability sampling method with a sampling technique that is simple random sampling which is a way of taking samples with all objects or elements of the population have the same opportunity to be selected as a sample. The questionnaire is a number of written questions that are used to obtain information from the respondent in the sense of a report about his personality, or things he knows. The questionnaire used was open questionnaire and closed questionnaire.