Reviewerly/exHarmony huggingface dataset:
Perspectives of the development of world economy in the blockchain conditions and Big Data

Abstract Blockchain is a concept that tends to revolutionize the world of finance in a technological leap that allows fast, secure and decentralized transactions. The Blockchain technology is used in virtual coins (bitcoin) conditions, with a high innovation potential, applicable in various areas, with the advantage of storing databases, resulting in an unprecedented level of transparency in the private or public area. Interestingly, under the bitcoin conditions, the black chain system uses a decentralized peer-to-peer payment system. Practically, the bitcoin can be considered as the most appropriate triple game accounting system. All of these considerations are developing in the big data era, which is defined as a large, diverse, high-volume information base requiring new forms of processing. Big data is important for businesses because based on these, strategic and marketing decisions can be made to optimize the activity in the market conditions and consumer preferences. European Union directives provide for measures to ensure the development of all states and, in this context, the community. At the same time, some measures provide for a more accelerated development for states with a low accession. For this, funds have been made from which important amounts are allocated to these states. The complex development of the European Union aims, in fact, to improve the quality of life (standard of living) in all Member States. At the European community level there are databases usable in economic analyzes. Also, Eurostat is the institution with the most complex databases. Recently, the Conference of the Directors of the Institute of Statistics in the European States analyzed the perspective of calculating the indicators in the context of the big data to be implemented. The article focuses on the concrete study of the use of large data in the calculation of the indicators that underlie the comparability between the EU Member States.
Performance Analysis of PL/SQL Query Optimization Techniques

Optimization in PL/SQL Programming is the preeminent aspect for database related applications built using PL/SQL code. PL/SQL statement/Query can be written in different ways for fetching the same output, but the most suitable technique should be considered when performance is a crucial factor, since processing time of the query may have significant variance, starting from a fraction of a second ending to hours, depending upon the method preferred. The main aim of query optimization is to find a solution that processes a specific query in minimum optimum time duration. This paper articulates different ways to optimize the performance of SQL queries and PL/SQL scripts by reducing the time complexity and number of context switches between SQL Engine and PL/SQL Engine.
Augmented Reality in the Development of a Virtual Chemistry Laboratory

Currently the use of virtual learning environments is an area of great importance in education in Mexico, the use of information technologies and computing, is currently one of the main axes in basic education. This paper shows an introduction on the use of augmented reality, which is a technology that mixes real images with real-time digital information and that allows the use of virtual objects in conjunction with reality, in this case, in conjunction with the area of education, as well as an analysis of related works, the development of a virtual laboratory of chemistry as a mobile application with Augmented Reality, which focuses on high school education, this application was developed using Unity and Vuforia, finally The results are shown on a usability test by students who used a first version of the application, as well as an evaluation by the teachers of the application.
Suspicious Bank Card Transaction Recognition Based on K-means Clustering and Random Forest Algorithm

Suspicious transactions are hidden in thousands of massive transaction data, causing incalculable losses and risks, but the detection is very difficult. In terms of how to effectively explore and identify suspicious transactions from massive transaction data accurately and quickly, this paper adopts the method based on the combination of k-means algorithm and random forest algorithm to solve the problem of data imbalance in the identification of suspicious transactions in bank accounts, and proposes an effective suspicious transaction detection model. At the same time, the AUC(Area Under Curve) and Recall indicators such as the unbalanced data classification standard of performance evaluation, and finally to Kaggle data platform for the bank account of suspicious transactions data set, the results show that the proposed detection model of performance evaluation index AUC increased by 5%, F1-measure increases by 1%, show that the method has some reference value to the suspicious transactions recognition, limited information utilization rate is higher, which makes all kinds of Banks prediction speed and accuracy of suspicious transactions events get improved, can to some extent, reduce the operating cost and risk of the banking sector.
GENDER EQUALITY IN ONLINE ENGLISH BOOK IN READING AND WRITING MATERIALS

This study is to find out whether the writing and reading material is gender biased in the online English book published by British Council. The researchers used qualitative method by using content analysis technique. The data are collected through document review. The research focused on the analysis of six aspects which suggested by Logsdon, they were number of female/male in character, in the linguistic Equal on she and he as pronouns, one’s profession, gender role and behaviors, female and male on which focus on public and domestic role, female and male which focus on art talent, sport ability, and intellectual competence in art and sport in online English book. The result of research showed that the percentage of female is higher than male in the aspects female pronouns in writing material, gender roles (public role) in reading material, art, and sport talent in both of reading and writing material.  And the percentage of male are higher than female in the aspects  male characters in reading material, female pronouns in reading material and intellectual competence in reading material. It can be concluded that online English books written by the British Council are still found with inequality gender.
Semantic Recommendations and Topic Modeling Based on the Chronology of Romanian Literary Life

As part of the Romanian Academy’s effort aimed at underlining the importance of events centered on national authors and writings across time, the Chronology of Romanian Literary Life (also referred to as CVLR) is a centralized text repository which contains all important literature-related events that occurred after World War II. The current work presents an approach to capture topics’ evolution across time and helps learners by recommending events from the chronology on a given topic, based on a subset of 24 years of the CVLR. Our method combines techniques from information retrieval, topic modeling using LDA (Latent Dirichlet Allocation), and recommender systems to improve e-learning centered on Romanian literature. The most frequent topics in each year are ranked in order to identify and visualize the main interests in literature across time periods. Recommendations are performed in order to facilitate the exploration of the chronology, as it is currently indexed only by event dates.
A Survey on e-Sarthi: Your Safety our Concern

The majority of road accidents happen because of driver behavior and fault. Vehicle accidents not only cause death and injuries, but they are also reasons for financial losses and low productivity. The careless behavior of the driver also puts other drivers at risk. Driver drowsiness and have become important factors in accidents. So there is a need for the system that detects the drowsiness of the driver and alerts him. This paper gives a survey of the techniques used by the researcher for detecting driver's behavior in real-time while driving and abstract view of the proposed system that we are going to implement to analyze the driver's behavior by detecting drowsiness and yawning.
Towards a Fast NVMe Layer for a Decomposed Kernel

Operating system (OS) kernel extensions, particularly device drivers, are one of the primary sources of vulnerabilities in commodity OS kernels. Vulnerabilities in driver code are often exploited by attackers, leading to attacks like privilege escalation, denial-of-service, and arbitrary code execution. Today, kernel extensions are fully trusted and operate within the core kernel without any form of isolation. But history suggests that this trust is often misplaced, emphasizing a need for some isolation in the kernel. We develop a new framework for isolating device drivers in the Linux kernel. Our work builds on three fundamental principles: (1) strong isolation of the driver code; (2) reuse of existing driver while making no or minimal changes to the source; and (3) achieving same or better performance compared to the nonisolated driver. In comparison to existing driver isolation schemes like driver virtual machines and user-level device driver implementations, our work strives to avoid modifying existing code and implements an I/O path without incurring substantial performance overhead. We demonstrate our approach by isolating a unmodified driver for a null block device in the Linux kernel, achieving near-native throughput for block sizes ranging from 512B to 256KB and outperforming the nonisolated driver for block sizes of 1MB and higher.
Welcome to LAC/Bienvenue à BAC: A New Bilingual NACO Partner

In 2018, the national, bilingual authority file maintained by Library and Archives Canada (LAC), called Canadiana Authorities, underwent major changes when the internally-developed Integrated Library System (ILS) AMICUS was decommissioned and OCLC’s WorldShare Management Services (WMS) was adopted as a replacement. As a part of the transition, LAC split its single, bilingual authority file Canadiana Authorities into separate English and French language files and joined Name Authority Cooperative Program (NACO) in order to manage its English-language authority records. This has been a significant change that has challenged the organization to rethink everyday practices while maintaining its commitments to the Canadian and global library community. This paper discusses this national library’s history of bilingual cataloging, the reason for the changes, and the attempt to ensure that the two files “talk” to each other.
Quadrotor Tracking Control Based on Optimized Fuzzy Logic Controller

A quadrotor is required by the military to conduct surveillance and monitor in the border and coastal areas of Indonesia. To do so, it requires a tracking path. The widely used tracking control to follow the path is fuzzy logic controller algorithm. This algorithm is applied to control the quadrotor when it follows the trajectory. The problem is that it takes a long rise time; moreover, there is an error on the steady time which generates overshoot. The error member set of the fuzzy logic controller was optimised to obtain more optimum results. The proposed algorithm showed that the quadrotor moved on a predefined trajectory in 1.5 seconds rise time, and 1.9 seconds steady-state time, and there was no overshoot. The problem is that it takes long rise time, generates Error on the steady-state time and there is overshoot. The research aims to accelerate the quadrotor, remove the Error on the steady-state time and reduce overshoot. It optimises the Error member set of the fuzzy logic controller to obtain a more optimum result. The research result showed that the quadrotor moved on a predefined trajectory in 1.5 seconds rise time. The steady-state time of the quadrotor was reached at the 1.9th seconds. The proposed algorithm enables the quadrotor to perform faster rise time, remove Error on the steady time and generate minute overshoot that is 0.1.
Development of Pressure Fryer for Fried Chicken

Fried chicken is one of the Malaysian favorite food especially for students who are most of them having a lunch or dinner with a cup of rise. Buying the fried chicken is quite expensive if they buy most every day. The way how to cut the cost is fry the chicken by themselves. However, many of them are not trained how to fry a chicken with a good condition. Therefore, this project is intended to overcome the stated problem by designing and developing a pressure fryer. The designed machine has following a basic design process started from identification of needs, conceptual design, embodiment design and detail design. Meanwhile, for proof-of-concept testing, the proposed machine concept has been developed to test the functionality and capability. Several activities have been included in discussion. As a summary, the pressure fryer has been successfully designed and verified based on the proof-of-concept testing. This machine can be used for frying a chicken with a good condition and suitable for home or individual purpose and also can do bigger task if the size of the machine is scaling up depend on the required chicken’s quantity.
Deep Neural Networks for Detection of Credit Card Fraud

The purpose of this paper is to present preliminary results from ongoing study, concerning application of Deep Neural Networks (DNN) to the detection of credit card fraud. The main approach is testing the change of different archi-tectural parameters of the neural network. The influence of the change on the performance and convergence of the network is measured. Some of the chosen parameters are the depth of the network, the width of each layer and the chosen activation functions in each layer. The main results of this study indicate that deep neural networks with moderate number of hidden layers in combination with techniques of oversampling are performing markedly better in detecting fraudulent transactions than networks with only one hidden layer. The used sample dataset is imbalanced, which means that the DNN training on the dataset has tendency to overfit. The results of this study are useful for other researchers and practitioners who try to analyze real datasets in order to detect card frauds.
Skip Gram Model Base Entropy Reduction using Vision based Page Segmentation for Web Mining

Lots of web applications, information recovery, for example, info extraction and then programmed page adjustment is able to profit by this particular structure. Extraction of web information from the full web page will be the intensive assignment to recover the substantial info because they’re website programming language subordinate. This model prepared to identify both marked picture info and in addition semantic info gathered from an annotated content. Semantic learning enhances the hit rates of up to eighteen % crosswise over a good many novel marks never ever noticed through the visible design. Given a content corpus, SKIP GRAM goes for Prompting term portrayals which are good at foreseeing the environment words surrounding an objective word. The primary goal of this paper is analyzing the Vision Based Programming Language Independent Approach Trained with Skip Gram, to assess the VIPS algorithm to assess the Vision Based Page Segmentation algorithm for Web Mining and also To Implement a strong Web Data Extraction from Semi Structured Source.
The Impact of Role Stress in Organizations on Employees' Innovative Abilit

With the rapid development of economic globalization, enterprise competition is increasingly fierce, and innovation is the first driving force for its sustainable development. The essence of enterprise innovation is employee innovation. In order to achieve core competitive advantages, enterprises should actively encourage employees to innovate. Taking role pressure as an antecedent variable, explore its impact on employee innovation ability. In addition, emotional commitment is introduced as a mediator variable to explore how it affects employee innovation. First, the theoretical hypothesis is proposed by reviewing the relevant literature. Secondly, the questionnaire survey method is used to conduct research on the employees, and the data is analyzed and hypothesized. Finally, conclusions are drawn. It is hoped that the research results will help enterprises better relieve the pressure of employee roles and improve their innovation ability.
An Ontological Analysis and Natural Language Processing of Figures of Speech

The purpose of the current paper is to present an ontological analysis to the identification of a particular type of prepositional figures of speech via the identification of inconsistencies in ontological concepts.Prepositional noun phrases are used widely in a multiplicity of domains to describe real world events and activities.However, one aspect that makes a prepositional noun phrase poetical is that the latter suggests a semantic relationship between concepts that does not exist in the real world.The current paper shows that a set of rules based on WordNet classes and an ontology representing human behaviour and properties, can be used to identify figures of speech due to the discrepancies in the semantic relations of the concepts involved.Based on this realization, the paper describes a method for determining poetic vs. non-poetic prepositional figures of speech, using WordNet class hierarchies.The paper also addresses the problem of inconsistency resulting from the assertion of figures of speech in ontological knowledge bases, identifying the problems involved in their representation.Finally, it discusses how a contextualized approach might help to resolve this problem.
The use of education from neurosciences

The general objective of this research is the use of new technologies in education starting from neurosciences since a study of the student must be carried out to identify their abilities and apply new knowledge techniques and generate new learning. Each of the teachers nowadays should consider the use of ICT, as support in the classroom as it allows students to use this software’s in the class that contains learning and then generate the same new knowledge that each one can evoke. Whenever necessary. The result that has been obtained is to identify software that contributes significantly to the teaching-learning processes in the different areas since by teaching the chairs with innovation, the interest of the students is aroused.
Brecciation in the Ontario mine, east flank ore bodies, Park City district, Utah.

A study of the brecciation in the Ontario Mine, East Flank Ore Bodies indicates a variety of structural types of brecciation are present. These are; (1) tectonic breccias, (2) bedded or stratiform breccias, (3) breccia pipes, (4) pebble dikes, and (5) igneous contact breccias. Multiple ages of brecciation were recognized in the Ontario Mine. Pre-mineral breccias are distinguished by the replacement of both the fragments and matrix with sulfides and replacement with silica associated with the ore fluids. Post-mineral brecciation includes tectonic breccias and collapse structures. Three types of brecciation are distinguished on the basis of origin. These are; (1) injection breccias, (2) collapse breccias, and (3) tectonic breccias. A significant amount of mineralization is localized by breccition. However, not all of the breccias are mineralized. Pre-mineral brecciation along the 1809 Ore Horizon and the North Ore Zone has provided open structures which form the host rocks for these ore bodies. It is believed that some of the pre-mineral breccias will be useful as exploration guides in the Ontario Mine.
Full-field heterodyne white light interferometry

In order to solve the problem that the displacement accuracy of linear displacement mechanism is too high in traditional white light interferometry, this paper proposes a full-field heterodyne white light interferometry. The technology mainly uses the white light interference signal with difference frequency as the light source to realize the high-precision detection of the coherent peak position under the conditions of large push step and low push precision. In this paper, the mathematical model of white light heterodyne interference is established firstly, and then the overall system design scheme is proposed according to the light intensity signal characteristics provided by the mathematical model. Then the feasibility of the measurement scheme is verified by experiments. At the end, theoretical analysis and data comparison are carried out for the influence of various errors on the calculation accuracy of the algorithm. The results of error analysis show that the white-light heterodyne interferometry technology provides higher measurement accuracy and better anti-interference performance, effectively reducing the strict dependence of traditional white light interferometry on the accuracy of linear displacement mechanism, and is an optical free-form surface detection technology. More solutions are available.
InDoCaS: A process for domain engineering in software production lines with a quality approach

This article proposes a process for domain engineering in software production lines based on Software quality called InDoCaS. The main disciplines of this process are the analysis, design and implementation of the domain. The process proposed here can be used in the software production line development approach and can be instantiated for a specific domain and the produced software assets can be reused to generate a product from a particular domain family. The concepts of: development processes, reuse of software assets, domain engineering, variability models, software production lines and Bayesian learning techniques are applied to define the way in which these applications are adapted at runtime to the applications. environment changes. These software variability and adaptability requirements represent an interesting challenge within software engineering. The contribution of this paper to the area of software development based on software production lines is to propose a process for domain engineering with a quality approach that will allow the specification of the quality requirements of the domain application families to be formalized, presenting details about the activities of analysis, design and implementation of the base architecture and its refinement.
Identifying Outliers for Climatology Time Variant Series with Sliding Window

It is important to identify outliers for climatology series data. With better quality of data decision capability will improve which in turn will improve the complete operation. For the same an algorithm, which is based on sliding window prediction is proposed in this paper. The time series are parted in accordance with the size of sliding window. Then a prediction model is rooted with the help of historical data to forecast the new values. There is a pre decided threshold value which will be compared to the difference of predicted and the value measured. If the difference is greater enough than the value of defined threshold then that specific point can be treated for outlier. Results from experiment are showing that the algorithm is identifying the outliers for climatology time variant series data and also remodeling the correction efficiency.