Reviewerly/exHarmony huggingface dataset:
Student Attendance Information System Based On Android Using T Test

This Android-based attendance system provides information on student attendance to parents automatically every class hour so that parents can monitor their children's attendance at school. The purpose of this study is to convey information from the school to parents regarding student attendance so that attendance and information to parents are effective. The method used in this study is the method for testing the questionnaire on the system used, namely the method of independent sample test (T test). For testing the system in this study using the blackbox method so as to know which functions are running and not running on the system. The results achieved are that student attendance is done digitally on the smartphone of each teacher and student attendance information is automatically entered on the parent's smartphone every lesson so that parents can find out their child's presence every day. The hypothesis in this study is valid or accepted because the implementation of the Android attendance system is more effective than the previous system. help the teacher in recap attendance which will be seen by the attendance data in the admin.
Enhanced Privacy and Security of Voters' Identity in an Interplanetary File System-Based E-Voting Process

Blockchain technology is in demand due to its key properties, such as immutability, transparency, distributed storage, and non-centric controls. The election is the primary process for forming a government at local, state, or federal levels in any democratic country. A fair election increases people’s faith in their government. An electronic voting system is a safer solution during this pandemic for the democratic voting system. However, the electronic voting system has a number of potential issues, including security and privacy breaches, the fear of cyber-attacks, the hijacking of the session, and identity theft. Using Blockchain, we can overcome many security and privacy issues as Blockchain uses a cryptographic hash and digital signatures for sending and verifying transactions in the peer-to-peer Blockchain network. Identity management is a critical issue in the election system as many fake voters are available and in the traditional election system, many fake votes are counted. We proposed a system that generates the identity of voters using the tokens and stores them in the interplanetary file system (IPFS). The proposed system provides the storage of tokens and verification of tokens during various stages of polling. The proposed system implemented using the IPFS, as well as the Elliptic Curve Digital Signature Algorithm (ECDSA) for the digital signature, and verification, and SHA-256 as a cryptographic hash. IPFS is used to store data in a distributed manner using the connected nodes in the network. In the proposed system, we use Go IPFS to store the files in Distributed Ledger Technology (DLT). IPFS can store any large file within any format. By splitting the user identity files, we can secure the data and privacy of voters in the Blockchain electronic voting system.
Applications to Facilitate Web-Based online Transactions

small business that produces sales of coconut and coconut ice. Regarding the sale, the sales transaction is still in place, does not have online sales media with the shop owner wanting to create a web. From this research, the authors are interested in making web sales transactions online. To solve this problem, a method is used, namely Waterfall, which is very suitable in making the Web because sequentially starting from data analysis, design, coding, testing, implementation, maintenance. So the purpose of this study is to implement online sales transactions. The results of the research Small business can serve online sales transactions
A Static Dictionary-Based Approach To Compressing Short Texts

In this study, Static Dictionary Compression (SDC) method, which is an approach developed to compress short texts, is proposed. The word-based static dictionaries used in this approach were obtained from clusters formed as a result of running a clustering method repeatedly until certain criteria are met. Short text is compressed with the dictionary that has the largest number of words in common with it. It has been shown by tests conducted with datasets containing short texts in 6 different languages that the proposed method compresses better than the general purpose compression methods Gzip, Bzip2, Zstd and PPMd. In the tests made with the data set containing only English short texts, it has been shown that the SDC method can compress better than the smza, shoco and b64pack methods used to compress short texts, and Brotli, which gives good results in short texts because it uses a static dictionary.
Computational Models of Evolutionary and Swarm Bio Heuristics (Review)

omputational models of evolutionary and swarm algorithms using nature-inspired mechanisms of self-organization and learning are presented. Experimental results are presented for the problem of placing a graph on a plane with the minimum total length of the graph edges.
Designing The User interface of An android-Based Garbage Bank Application Based on User Experience With The User Centered Design Method

Garbage is one of the problems in Village, at some points there is a buildup of rubbish which is quite alarming and pollutes the surrounding environment. Therefore the government intention of Village in the next few years seeks to overcome these problems by building a technology-based waste bank, one of which is the use of applications as an alternative in carrying out environmental management facilities and communication media with the community in providing environmental information. Before entering into the development of software systems the user interface design process is very important to do, because the design of the user interface is designed so that the designed software system can present the appearance of an application by showing the flow and the workings of the application. So that if the design is detailed, the coding process carried out by the developer can be achieved mechanically. In designing the user interface conducted in this study the User Centered Design (UCD) method is used in which the process will involve potential users in the early to late stages of development so that potential users can provide input regarding the interface designed. To find out the level of success of the user interface design that is designed can be seen in the measurement results in a user interface that meets aspects of usability and user experience. The results of this study are to design the user interface design of an Android-based garbage bank in village that pays attention to aspects of usability and meets 6 values of user experience.
European Court of Human Rights Case Law on Genetic Information in the Scope of International Biomedical Law

The aim of the study is to analyze the case law of the European Court of Human Rights on genetic information in the scope of international biomedical law, as expressed in the International Declaration on Human Genetic Data and the Convention on the Protection of Human Rights and Human Dignity in the Field of Application of Biology and Medicine. The Court held that the genetic information is protected under the law of the Convention on Human Rights and Fundamental Freedoms. The model of the right to respect for private life is reflected in its shape, as the Court noted in the Van der Velden v. The Netherlands and S. and Marper v. The United Kingdom cases. It leads to the conclusion that the provision of Article 8 of the Convention provides the protection of genetic information, subject to certain restrictions that are “in accordance with law” and “necessary in a democratic society”. Such conclusion is in compliance with art. 12, art. 17 (b) art. 21 (c) of the International Declaration on Human Genetic Data, and art. 11 of the Convention for the Protection of Human Rights and Dignity of the Human Being with regard to the Application of Biology and Medicine.
A Many-Objective Simultaneous Feature Selection and Discretization for LCS-Based Gesture Recognition

Discretization and feature selection are two relevant techniques for dimensionality reduction. The first one aims to transform a set of continuous attributes into discrete ones, and the second removes the irrelevant and redundant features; these two methods often lead to be more specific and concise data. In this paper, we propose to simultaneously deal with optimal feature subset selection, discretization, and classifier parameter tuning. As an illustration, the proposed problem formulation has been addressed using a constrained many-objective optimization algorithm based on dominance and decomposition (C-MOEA/DD) and a limited-memory implementation of the warping longest common subsequence algorithm (WarpingLCSS). In addition, the discretization sub-problem has been addressed using a variable-length representation, along with a variable-length crossover, to overcome the need of specifying the number of elements defining the discretization scheme in advance. We conduct experiments on a real-world benchmark dataset; compare two discretization criteria as discretization objective, namely Ameva and ur-CAIM; and analyze recognition performance and reduction capabilities. Our results show that our approach outperforms previous reported results by up to 11% and achieves an average feature reduction rate of 80%.
Reflections towards a transformative movement for radical democratic and ecological pedagogy

In many initiatives, radical democratic and ecological pedagogy is developed in relation to relatively static initiatives such as classrooms, community action research projects, civic engagement programs, or other institutional platforms. While such settings can provide good platforms, I argue that when they are offered in relatively static terms, they inadvertently undermine the expansive pedagogical possibilities for theory and praxis towards which they aspire. I theorise more dynamic and powerful educational possibilities in relation to platforms whose basic character, trajectories, and networks are themselves co-created over time by those whose agency they nurture. Thus, students and faculty become integrally engaged in the ongoing reformation and expansion of the pedagogical and institutional platforms through which democratic and ecological consciousness and agency are cultivated. Such pedagogy is thus conceived as a vital movement rather than a program. This chapter explores this proposition both theoretically and in relation to a university-wide movement for democratic ecological pedagogy and institutional change in which the author was a collaborative leader.
Compositional Generalization in Dependency Parsing

Compositionality-the ability to combine familiar units like words into novel phrases and sentences-has been the focus of intense interest in artificial intelligence in recent years.To test compositional generalization in semantic parsing, Keysers et al. (2020) introduced Compositional Freebase Queries (CFQ).This dataset maximizes the similarity between the test and train distributions over primitive units, like words, while maximizing the compound divergence-the dissimilarity between test and train distributions over larger structures, like phrases.Dependency parsing, however, lacks a compositional generalization benchmark.In this work, we introduce a gold-standard set of dependency parses for CFQ, and use this to analyze the behavior of a state-of-the art dependency parser (Qi et al., 2020) on the CFQ dataset.We find that increasing compound divergence degrades dependency parsing performance, although not as dramatically as semantic parsing performance.Additionally, we find the performance of the dependency parser does not uniformly degrade relative to compound divergence, and the parser performs differently on different splits with the same compound divergence.We explore a number of hypotheses for what causes the non-uniform degradation in dependency parsing performance, and identify a number of syntactic structures that drive the dependency parser's lower performance on the most challenging splits.
Website-Based Village E-Marketplace System Prototype

Many MSMEs in the village of Cimara are still marketing conventional or simple ways such as offering their products door to door, placing their products in stalls and through events such as exhibitions, so that the scope of product sales is narrow, namely in the Sumedang area, because of that the SMEs experiencing difficulties and slow in expanding their marketing horizons. Based on these problems, the aim of this research is to design an e-marketplace system managed by the Cimara village goverment as one of the additional sales media for MSMEs in the Cimara village. The method used in designing or developing this e-marketplace system is the prototype method. With the prototype method the user can interact with the prototype model that was developed through the evaluation phase so that the writer can gather information from the user regarding the system being developed because the prototype describes the initial version of a system. The results achieved from this research are the website-based MSME Cimara village e-marketplace system. With the existence of this e-marketplace system, it is a step forward for MSMEs in Cimara village, especially in terms of product marketing, because with this e-marketplace system, MSME owners in Cimara village can market their products more broadly
Automated Machine Learning Platform

With the rapid development of information technologies and the widespread use of the internet, the volume and diversity of data has also increased. Meaningful information and important results can be obtained by processing this data, which is expressed with the concept of big data. In this study, a machine learning platform that can automatically learn from data sets with different data types and dimensions has been developed. When the dataset of any field is given as an input to the developed automatic machine learning platform, the most appropriate machine learning model is determined. With this platform, which has a Web interface that can be easily used by people who are experts in their field but do not have sufficient knowledge in the field of machine learning and data science, the most suitable machine learning model for the data set is suggested to the users and training and test results for different models can be obtained and compared. The experimental studies have shown that the developed platform is successful in knitting a machine learning model suitable for the dataset.
Integrating Technology that Uses Modified SAMR Model as a Pedagogical Framework in Evaluating Learning Performance of Undergraduates

This is a case study on the integration of technology using a modified SAMR (Substitution, Augmentation, Modification, Redefinition) model as a pedagogical framework in teaching and learning in a private college in Melaka, Malaysia on a chosen topic in Business Communication.The study was conducted in Summer, 2019.This is a quantitative study with two groups which are control and experimental groups.The control group had gone through the traditional teaching method while the experimental group learned through technology.The model was incorporated with Bloom's Taxonomy and TPACK for credibility and reliability.All four stages of the SAMR Model were investigated for the presence of content, pedagogy, and technology.The study identified that there was the presence of content, pedagogy, and technology in the stages of augmentation, modification, and redefinition while pedagogy and content were absent in the substitution level.However, the integration of technology using the proposed pedagogical framework improved student performance in the last three stages of augmentation, modification, and redefinition with positive results.Overall, the study has evidence that the modified SAMR Model had enhanced and improved student performance.It is hoped that the outcome of this research provides valuable insight and guidance to those who want to integrate technology into the teaching and learning process.
Real-time AI for Enterprise Workloads: the IBM Telum Processor

Next generation Z processor is optimized to run enterprise workloads with embedded real time AI insights.
The observer’s perspective determines which cues are used when interpreting pointing gestures.

Though ubiquitous in human communication, pointing gestures are often misunderstood. This study addressed how the observer's perspective affects pointing perception. More specifically, we tested the hypothesis that two different visual cues-namely (a) the vector defined by the pointer's arm or finger and (b) the pointer's index finger position in the observer's visual field-determine pointing perception and that their relative influence depends on the observer's perspective. In three experiments, participants judged the location at which a virtual or real pointer was pointing from different viewpoints. The experiments show that the observer perspective has a considerable effect on pointing perception. The more the observer's gaze direction is aligned with the pointing arm, the more observers rely on the position of the pointing finger in their visual field and the less they rely on its direction. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
How to develop your network with Python and Keras

Chapter Contents: 7.1 Introduction 7.1.1 TensorFlow and Keras 7.1.2 Tensors 7.2 Google Colaboratory 7.2.1 How to work with GPU? 7.2.2 How to connect Google Drive? 7.3 Examples 7.3.1 Noise filtering 7.3.1.1 Step 1 — Define a generator for the dataset 7.3.1.2 Step 2 — Build a model 7.3.1.3 Step 3 — Train and test the model 7.3.2 Classification 7.3.2.1 Step 1 — Define a generator for the dataset 7.3.2.2 Step 2 — Build a model 7.3.2.3 Step 3 — Train and test the model 7.3.3 Detection 7.3.3.1 Step 1 — Define a generator for the dataset 7.3.3.2 Step 2 — Build a model 7.3.3.3 Step 3 — Train and test the model 7.4 Conclusions References
Alternative approach to find optimal solution of assignment problem using Hungarian method by trapezoidal intuitionistic type-2 fuzzy data

Now a day’s uncertainty is a common thing in science and technology. It is undesirable also. Based on alternative view, it should be avoided by all possible means. Based on modern view uncertainty is considered essential to science and technology, it is not only the unavoidable plague but also it has impacted a great utility. Fuzzy set theory mainly developed based on inexactness, vagueness, relativity etc. fuzzy set may be used in mathematical modelling in every scientific discipline. It can also use for improving the generality of analytical solution. It has many uses in various streams like -operation research, control theory differential equations, fuzzy system reliability, optimization and management sciences etc. In this paper we first describe Trapezoidal intuitionistic Type 2 fuzzy number(TrIT2FN) with arithmetic operations and solve an assignment problem using Hungarian method for Trapezoidal intuitionistic Type 2 fuzzy number (TrIT2FN).
On relations in science: the case of the scientific journal editorial board

This article analyses the connections between members of the editorial board of a scientific journal which are formed based on their reviews of scientific articles. It is shown that the connections can be represented as a graph. The research uses the data for six years of article reviewing in the scientific and technical Journal of "Almaz — Antey" Air and Space Defence Corporation. The methods of analysis are combinatorics and graph theory, as well as the relevant graph characteristics: adjacency matrix, incidence matrix, reachability matrix, graph fullness and connectivity, nearest neighbours graph and graph spanning tree. It is shown that cooperation of the reviewers of the Journal helps plot a connected graph with links between any two vertices, i.e. between any reviewers. The graph is analysed and the methods of its application to calculate the Journal’s scientometric indicators are demonstrated. As the research reveals, a journal that publishes articles in numerous disciplines forms connections between all reviewers and this parameter can be indicative of interchangeability within the scientific fields or, conversely, of a joint work in this scientific field when reviewing manuscripts. Based on the research results, it is possible to search for new reviewers in the areas where competencies are underdeveloped. And by the areas where competencies are strong, we can determine the core competence of the reviewers of a scientific journal, reflecting the main focus of the evaluated scientific research. The work resulted in the formulated scientometric indicators of the journal, which can be used to search for and involve new reviewers or to represent data on a strong team of reviewers on a specific topic, as well as on a new scientific field just emerging for research.
Small-Sized Vehicle Detection in Remote Sensing Image Based on Keypoint Detection

The vehicle detection in remote sensing images is a challenging task due to the small size of the objects and interference of a complex background. Traditional methods require a large number of anchor boxes, and the intersection rate between these anchor boxes and an object’s real position boxes needs to be high enough. Moreover, the size and aspect ratio of each anchor box need to be designed manually. For small objects, more anchor boxes need to be set. To solve these problems, we regard the small object as a keypoint in the relevant background and propose an anchor-free vehicle detection network (AVD-kpNet) to robustly detect small-sized vehicles in remote sensing images. The AVD-kpNet framework fuses features across layers with a deep layer aggregation architecture, preserving the fine features of small objects. First, considering the correlation between the object and the surrounding background, a 2D Gaussian distribution strategy is adopted to describe the ground truth, instead of a hard label approach. Moreover, we redesign the corresponding focus loss function. Experimental results demonstrate that our method has a higher accuracy for the small-sized vehicle detection task in remote sensing images compared with several advanced methods.
Phoenix: A Scalable Streaming Hypergraph Analysis Framework

We present Phoenix, a scalable hypergraph analytics framework for data analytics and knowledge discovery that was implemented on the leadership class computing platforms at Oak Ridge National Laboratory (ORNL). Our software framework comprises a distributed implementation of a streaming server architecture which acts as a gateway for various hypergraph generators/external sources to connect. Phoenix has the capability to utilize diverse hypergraph generators, including HyGen, a very large-scale hypergraph generator developed by ORNL. Phoenix incorporates specific algorithms for efficient data representation by exploiting hidden structures of the hypergraphs. Our experimental results demonstrate Phoenix’s scalable and stable performance on massively parallel computing platforms. Phoenix’s superior performance is due to the merging of high-performance computing with data analytic.