Reviewerly/exHarmony huggingface dataset:
Problems of human being as a philosophic object in information context of gymnasium social development

The topic of humanities in context of information society development (teaching experience in high school) is extremely relevant, as every young person wants to master the problem as mean of life, its filling with meanings that must be explained in simple words. The problems of philosophy in the gymnasium integrate individual humanities and give a thorough account of the major problems of life. Some topics are supplemented by the thematic realms of aesthetics, anthropology, philosophy of history, philosophy of law and state, philosophy of nature and technology, philosophy of religion. Analysis of Recent Studies and Publications - We draw on the recent work of Maria Furst and Jürgen Trinks "Philosophy", which presents the teaching of philosophy at the Austrian gymnasium; Carol Duke's "Tune in to Change"; R. Florida “Homo creative. As a new class is conquering the world”, which discusses the problem of forming a creative personality capable of working in an information society environment. The author draws on a number of works by V. Nikitenko, M. Maksimenyuk, O. Sosnin, and O.Punchenko, in which the creative elements of the information society are explored. Methods - analysis and synthesis, systemic, structural, which allowed to analyze and structure problems; axiological, anthropological, which made possible to analyze the personality and its orientation value; synergetic, which made possible to analyze information society as a complex of non-linear system. Highlighting previously unsettled parts of general problem addressed in this article. The basis of the research - new approaches that have arisen in modern philosophy and changed understanding of philosophy and forced teachers and students to rethink complexity of life problems, to find new approaches to philosophy, which studies the complex situation of man in the world, his attitude to the environment, and how a person is guided on a life path. The purpose of the assignment is to analyze the problems of being as an object of philosophic teaching of gymnasium in development context of the information society, so, the question of the world and subject. The purpose of the article is to conceptualize the teaching of philosophy in gymnasium in development context of information society.Research results. Proved that, originality of philosophic thinking lies in fact that is connected with object, subject and whole, encompassing both of them. It is revealed that, depending on where the direction of thinking is directed and where is the key point, it puts the subject's attitude to himself. The conditions to form an information society, requires formation of an information-creative personality life capabilities and create in such way type of society, are revealed, but it is necessary to find its own essence, its own structures and laws of being that define it.
Consequences of International Financial Reporting Standards Adoption in Africa: Evidence From Foreign Direct Investment

International Financial Reporting Standards (IFRS) Adoption makes financial reporting transparent by enhancing the comparability and the quality of the financial information which reduces the transaction cost and attract foreign direct investment (FDI). This consequently facilitates the effective economic decisions of investors and other market participants. In light of this, many developing countries, in Africa, have resorted to the mandatory-IFRS adoption to enhance the inflow of foreign capital. The study, therefore, aims at finding out the effect of IFRS adoption on FDI inflows. We investigate whether the adoption of IFRS really enhances the inflow of foreign direct investment in developing countries.We use the Fixed Effect regression model, and the sample consisted of 45 (30 IFRS adopted and 15 IFRS non-adopted) African countries from the period of 2000 to 2017. The evidence from our study shows that the adoption of IFRS leads to increased FDI inflows. Most research on international financial reporting standard and foreign direct investment did not control the time period. By conducting further analysis using the difference-in-difference analysis to control the time period, our results highlighted that FDI inflows is higher after the adoption of IFRS. The increase in the value of FDI is influenced by the time period.
TOWARDS GENERATING EXERCISE QUESTIONS WITH LOD FOR WEB-BASED INVESTIGATIVE LEARNING

Web allows learners to investigate any question to learn with a large number of Web resources.In such investigative learning, leaners are expected to investigate the question by navigating Web resources/pages to construct their knowledge and decomposing the question into sub-questions.In acquiring skills in such investigative learning, learners need to practice with exercise questions.However, it is hard to define correct knowledge to be constructed for the questions since Web-based investigative learning could result in diverse knowledge as correct one for the same question.Towards this issue, this paper proposes the method with Linked Open Data (LOD) for generating exercise questions, which includes an initial question and sub-questions to be decomposed from an initial question.These sub-questions are extracted and selected as keywords with LOD and Word2vec.This paper also reports a case study with the generation method.The results suggest that it is effective as scaffolding particularly for novice learners.
The Innovation Model of Educational Technology to Strengthen Boarding University Education in Disruptive Era

The disruptive era brings many changes as various kinds of disturbances to arise in various aspects of life, including education.Boarding university as an educational institution should be able to adjust to challenges of the disruptive era in order not to lose competitiveness.This study aims at finding the innovation model of educational technology to strengthen the existence of boarding university in the disruptive era.The study used a qualitative method.Data collection was carried out through observation and interviews with several stakeholders at the University of Darussalam Gontor as a boarding university.The result of this study found the innovation model of educational technology at the University of Darussalam Gontor that was influenced by four elements of innovation diffusion.The four elements are composed of innovation, communication with certain channels, time, and members of the social system.One of the innovations in educational technology was e-learning technology.The contribution of this research is the innovation model of educational technology to strengthen the existence of boarding university, University of Darussalam Gontor.
Feature Augmentation based Hybrid Collaborative Filtering using Tree Boosted Ensemble

Text of the abstract: Requirements for recommendation systems are currently on the raise due to the huge information content available online and the inability of users to manually filter required data. This paper proposes a Feature augmentation based hybrid collaborative filtering using Tree Boosted Ensemble (TBE), for prediction. The proposed TBE recommender is formulated in two phases. The first phase creates category based training matrix using similar user profiles, while the second phase employs the boosted tree based model to predict ratings for the items. A threshold based filtering is finally applied to obtain precise recommendations for the user. Experiments were conducted with MovieLens dataset and performances were measured in terms of Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). The proposed model was observed to exhibit MAE levels of 0.64 and RMSE levels of 0.77 with a variation level of ±0.1. Comparisons with state-of-the-art models indicate that the proposed TBE model exhibits reductions in MAE at 6% to 14% and RMSE at ~0.2.
A Conceptual Framework for Software Fault Prediction Using Neural Networks

Software testing is a very expensive and critical activity in the software systems’ life-cycle. Finding software faults or bugs is also time-consuming, requiring good planning and a lot of resources. Therefore, predicting software faults is an important step in the testing process to significantly increase efficiency of time, effort and cost usage. In this study we investigate the problem of Software Faults Prediction (SFP) based on Neural Network. The main contribution is to empirically establish the combination of Chidamber and Kemer software metrics that offer the best accuracy for faults prediction with numeric estimations by using feature selection. We also proposed a conceptual framework that integrates the model for fault prediction.
Exploring the Playground: Blockchain Prototype Use Cases with Hyperledger Composer

While the accounting profession determines the possible future impacts of Blockchain, universities will need to prepare students for a career using the disruptive technology. This necessitates hands-on training to teach the basics of modeling a Blockchain network. Hyperledger is an open source Blockchain advancement initiative hosted by The Linux Foundation (IBM n.d). Hyperledger Composer is a specific Hyperledger project that provides a framework and necessary tools to facilitate new Blockchain development. This proposal walks students through three use cases with the outcome of 1) familiarizing them with IBM's Hyperledger Composer (a virtual playground in which they can experiment with numerous Blockchains), 2) orienting them to the underlying code that drives Blockchains, and 3) improving their technological agility by directing them to manipulate the code and observe the functional effects.
Food Photo Enhancer of One Sample Generative Adversarial Network

Image enhancement is an important branch in the field of image processing. A few existing methods leverage Generative Adversarial Networks (GANs) for this task. However, they have several defects when applied to a specific type of images, such as food photo. First, a large set of original-enhanced image pairs are required to train GANs that have millions of parameters. Such image pairs are expensive to acquire. Second, color distribution of enhanced images generated by previous methods is not consistent with the original ones, which is not expected. To alleviate the issues above, we propose a novel method for food photo enhancement. No original-enhanced image pairs are required except only original images. We investigate Food Faithful Color Semantic Rules in Enhanced Dataset Photo Enhancement (Faith-EDPE) and also carefully design a light generator which can preserve semantic relations among colors. We evaluate the proposed method on public benchmark databases to demonstrate the effectiveness of the proposed method through visual results and user studies.
Investigating practices and perceptions of higher education students concerning the utilization of mobile devices in their studies

The present research studies the views of students, of the University of Patras, according to the use of mobile devices such as smartphones and tablets in the educational process. Answers(of closed and open types questions) of 98 students of various departments of the University of Patras was concentrated and analyzed. The majority of students own smart devices which they use to communicate with each other and to support their studies. The students perceive various obstacles to using mobile devices as well as problems in their use for academic purposes. Suggestions for the use of mobile devices in the educational process are discussed.
A DISTRIBUTED CONTENT ADDRESSABLE NETWORK FOR OPEN EDUCATIONAL RESOURCES

We introduce Content Addressable Resources for Education (CARE) as a method for addressing issues of scale, access, management and distribution that currently exist for open educational resources (OER) as they are currently developed in higher education.CARE is based on the concept of the distributed web (dweb) and, using (for example) the Interplanetary File System (IPFS) provides a means to distributed OER in such a way that they cannot be blocked or paywalled, can be associated with each other (for example, as links in a single site, or as newer versions of existing resources) creating what is essentially an open resource graph (ORG), and when accessed through applications such as Beaker Browser, can be cloned and edited by any user to create and share new resources.
Group Labeling Methodology Using Distance-based Data Grouping Algorithms

Clustering algorithms are often used to form groups based on the similarity of their members. In this context, understanding a group is just as important as its composition. Identifying, or labeling groups can assist with their interpretation and, consequently, guide decision-making efforts by taking into account the features from each group. Interpreting groups can be beneficial when it is necessary to know what makes an element a part of a given group, what are the main features of a group, and what are the differences and similarities among them. This work describes a method for finding relevant features and generate labels for the elements of each group, uniquely identifying them. This way, our approach solves the problem of finding relevant definitions that can identify groups. The proposed method transforms the standard output of an unsupervised distance-based clustering algorithm into a Pertinence Degree (GP), where each element of the database receives a GP concerning each formed group. The elements with their GPs are used to formulate ranges of values for their attributes. Such ranges can identify the groups uniquely. The labels produced by this approach averaged 94.83% of correct answers for the analyzed databases, allowing a natural interpretation of the generated definitions.
Alarm Filtering Method of Power Communication Network Based on Correlation Set

Abstract In order to find out the root from a large number of alarms of alarm events, we did a good study on the alarm’s characters of power communication network equipments, through which we found the alarm relevance sets. On this basis, we present a relevance-set based alarm filtering approach, which make the unnecessary and none-root alarms filtered much more quickly.
From AI to CI: A Definition of Cooperative Intelligence in Autonomous Driving

With the rapid development of deep learning, artificial intelligence (AI) has been widely used in many fields and gradually replaced a part of human jobs. However, the approach of improving intelligent capability of single agent is not enough to achieve complicated tasks in ever-changing environments. Cooperative intelligence (CI) is regarded as a promising way to solve this problem. In this paper, we scientifically define the three key problems of achieving cooperative intelligence, which are cooperative perception, cooperative decision and cooperative learning. We illustrate each problem with a scenario of autonomous driving as well as a brief survey of related research works. Meanwhile, we propose a system architecture and components design of cooperative intelligence system for autonomous driving.
Two classes of near-optimal codebooks with respect to the Welch bound

<p style='text-indent:20px;'>An <inline-formula><tex-math id="M1">\begin{document}$ (N,K) $\end{document}</tex-math></inline-formula> codebook <inline-formula><tex-math id="M2">\begin{document}$ {\mathcal C} $\end{document}</tex-math></inline-formula> is a collection of <inline-formula><tex-math id="M3">\begin{document}$ N $\end{document}</tex-math></inline-formula> unit norm vectors in a <inline-formula><tex-math id="M4">\begin{document}$ K $\end{document}</tex-math></inline-formula>-dimensional vectors space. In applications of codebooks such as CDMA, those vectors in a codebook should have a small maximum magnitude of inner products between any pair of distinct code vectors. In this paper, we propose two constructions of codebooks based on <inline-formula><tex-math id="M5">\begin{document}$ p $\end{document}</tex-math></inline-formula>-ary linear codes and on a hybrid character sum of a special kind of functions, respectively. With these constructions, two classes of codebooks asymptotically meeting the Welch bound are presented.
Cloud infrastructures for data sharing

This chapter offers the basis for understanding the origins of cloud computing and its importance toward medical data sharing. The concept of cloud computing is described through the Internet of Things (IoT) along with standard cloud models for enabling this concept. Popular cloud architectures are presented, including the Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS), as the three fundamental layers for establishing a cloud platform. Methods for developing web services are further presented along with tools and popular cloud vendors in healthcare. Cloud security issues, encryption protocols, and international security guidelines and standards are discussed. The most important technical challenges are also highlighted toward a secure, on-demand, federated cloud platform.
Developing Mobile Learning Media Integrated of Problem Based Learning In Chemical Equilibrium Materials at Unimed Chemical Education Study Program

This study aimed to understand level of feasibility of learning media mobile learning for special topic of chemical equilibrium; and to know the differences of the improvement learning outcomes of students is problem based learning in learning chemical equilibrium studied by using media of Mobile Learning developed with power -point.It used R & D method (Development Research) with model ADDIE.Sample selection using purposive sampling technique.The population in this study were college student S-1 of semester II of chemistry education study program taking elementary chemistry courses even semester 2018/2019 at State University of Medan.The sample in this research are two classes in the basic course chemistry of FMIPA UNIMED department semester 2 which have 25 students for each class.The research instruments are motivation questionnaire and objective test.Data were analyzed using descriptive method and statistical analysis with independent sample t-test.The result showed that: (1) the developed learning media of Mobile Learning was categorized with feasible to used but still needs to be revised and developed, (2) there was the difference improvement learning outcomes of students (N-gain of students) for special topic of chemical equilibrium that learned using media of Mobile Learning which had been developed in experimental class I was found higher than that in experimental class IIwith power-point media (74% > 63%).
Implementasi Keamanan Jaringan Komputer Local Area Network Menggunakan Access Control List pada Perusahaan X

In Company X, the use of the internet is a demand for workers. Therefore, an internet network is very much needed in a Company X. The absence of restrictions in the use of the internet network can interfere with the security and misuse of the internet network, for this reason the arrangements in the internet network are designed. One method used is the Virtual Local Area Network (VLAN) Access Control List (ACL) method that is applied to Company X. The Vlan Access Control List method is one of the techniques for requesting an internet network access or data communication and sending a number of data packets from one computer to another. The author resets the results proving that the Vlan Access Control List with the filtering and sharing method of internet connection users can filter and identify users who have restricted access to access other users or to servers in Company X to improve data security.
Recurrent neural network-based speech recognition using MATLAB

The purpose of this paper is to design an efficient recurrent neural network (RNN)-based speech recognition system using software with long short-term memory (LSTM). The design process involves speech acquisition, pre-processing, feature extraction, training and pattern recognition tasks for a spoken sentence recognition system using LSTM-RNN. There are five layers namely, an input layer, a fully connected layer, a hidden LSTM layer, SoftMax layer and a sequential output layer. A vocabulary of 80 words which constitute 20 sentences is used. The depth of the layer is chosen as 20, 42 and 60 and the accuracy of each system is determined. The results reveal that the maximum accuracy of 89% is achieved when the depth of the hidden layer is 42. Since the depth of the hidden layer is fixed for a task, increased performance can be achieved by increasing the number of hidden layers.
Model Classification Of Nominal Value And The Original Of IDR Money By Applying Evolutionary Neural Network

Indonesian Rupiah (IDR) banknotes have unique characteristics that distinguish them from one another, both in the form of numbers, zeros and background images. This pattern of each type of banknote will be modeled in order to test the nominal value and authenticity of IDR, so as to be able to distinguish not only IDR banknotes but also other denominations. Evolutionary Neural Network is the development of the concept of evolution to get a neural network (NN) using genetic algorithms (GA). In this paper the application of evolutionary neural networks with less input is able to have a better success rate in object recognition, because the parameters for producing neural networks are far better
Analyzing the Adoption Rate of Local Variable Type Inference in Open-source Java 10 Projects

Type Inference is used in programming languages to improve writability.In this paper, we will be looking more specifically at Local Variable Type Inference (LVTI).For those unfamiliar with LVTI, we will also give an in-depth explanation of what it is and how it works.There is a lot of debate surrounding Type Inference in modern day programming languages.More specifically, whether the costs associated with LVTI outweigh the benefits.It has found its way into many higher-level languages including C#, C++, JavaScript, Swift, Kotlin, Rust, Go, etc.In this paper, we will look at the usefulness of LVTI and its popularity since the release of Java 10.Our study will show that LVTI in Java has not received widespread adoption.We will also explain a possible reason for this, based on the information we have gather from our empirical study which involved statically analyzing 6 popular open source Java 10 projects.We will also discuss different scenarios in which Type Inference can obscure different programming errors.