Reviewerly/exHarmony huggingface dataset:
Analysis of the effect of annealing rate on the thinness film of BaZr0.4Ti 0.6O3 at 800°C for 2 hours

Abstrak. Ferroelektrik merupakan bahan yang mempunyai polarisasi spontan serta mempunyai kemampuan mengubah polarisasi internalnya dengan menggunakan medan listrik yang sesuai. Ferroelektrik juga diaplikasikan sebagai kapasitor. Material ferroelektrik buat dalam bentuk film tipis. Barium Zirconium Titanate (BZT) dengan komposisi BaZr0.4Ti0.6O3 dibuat menggunakan metode sol-gel. Substrat yang digunakan yaitu FTO yang telah di etching dan di lapisi BZT serta di annealing pada suhu 800°C selama 2 jam dengan kenaikan laju suhu annealing yaitu 5°C dan 10°C. Sampel di karakterisasi menggunakan XRD. Hasil karakterisasi XRD menunjukkan adanya puncak-puncak yang menandakan terdapat struktur kristal. Struktur kristal yang dihasilkan berada pada bidang 100 pada sudut 2θ = 22.78°, bidang 110 pada sudut 2θ = 32.17°, bidang 111 pada sudut 2θ = 38.42°, bidang 200 pada sudut 2θ = 47.73°. Struktur yang dihasilkan pada penelitian ini yaitu tetragonal dimana a = b = 3.91 nm dan c = 4.05 nm. Laju kenaikan suhu berpengaruh pada puncak Difraksi Sinar-X. Nilai FWHM untuk 5°C lebih kecil dari 10°C, ini menunjukan adanya kerapatan yang lebih besar saat di annealing dengan laju 5°C. Nilai ukuran kristal yang di dapat dengan kenaikan suhu 5°C dan 10°C pada bidang 100 yaitu 3.94 nm dan 3.22 nm. Ukuran kristal berbanding terbalik dengan nilai FWHM dimana laju kenaikan suhu annealing yang kecil menyebabkan ukuran kristal membesar. Abstract Ferroelectrics is a material that has spontaneous polarization and ability to change its internal polarization by using a suitable electric field. Ferroelectricsis also applied as a capacitor. The ferroelectric material is made in the form of a thin film. Barium Zirconium Titanate (BZT) with the composition BaZr0.4Ti 0.6O3 is prepared using the sol-gel method. The substrate used is FTO which has been etched and coated with BZT and annealed at a temperature of 800°C for 2 hours with a increase in the annealing temperature speed of 5°C and 10°C.Samples are characterized using XRD. The XRD characterization results show peaks indicating a crystal structure. The resulting crystal structure is in a plane 100 at an angle of 2θ = 22.78°, a plane 110 at an angle of 2θ = 32.17°, a plane 111 at an angle of 2θ = 38.42°, a plane 200 at an angle of 2θ = 47.73°. The resulting structure in this study is a tetragonal where a = b = 3.91 nm and c = 4.05 nm. The speed at which temperature increases has an effect on the peak of the X-Ray Diffraction.The FWHM value for 5°C is less than 10°C which indicates a greater density when annealed at a speed of 5 °C. The value of the crystal size obtained with an increase in temperature of 5°C and 10°C in the plane 100 is 3.94 nm and 3.22 nm. The crystal size is inversely proportional to the FWHM value where the small speed of the annealing temperature increase causes the crystal size to enlarge.Keywords: BaZr0.4Ti0.6O3 Thin Film, Speed of Annealing Temperature Increase, Sol-gel method, X-Ray Diffraction (XRD).
Monitoring of the Presence of Professional Expert Communities in the Russian Federation and Assessment of their Participation in the Development of the National Competence System

The article deals with the results of monitoring of the presence of professional expert communities in the Russian Federation, which have a particular impact on addressing socio-economic issues, including promoting the development of the national qualifications system in the country. The theoretical and methodological basis of the study is a criterial disclosure of the activities of expert communities based on the structure of the National Qualifications System. The study was carried out in 2020 and is a continuation of the previous works by the authors, implemented in 2016-2019, whose purpose was to monitor communities in a separate area of professional activity – personnel management. This study involved 56 communities, which were selected based on the participation of their representatives in one of ten Councils for Professional Competence (25% of all Councils currently operating in the Russian Federation). The results may be of interest to representatives of the institutions of the National Competence System, as well as the education system in the context of the influence of trade communities on the content of educational programs through professional standards created by community representatives, and to the professional expert communities themselves.
Desain dan Implementasi Deteksi WebShell Malicious Web Shell (Backdoor Trap)

We present a report on hacker attacks against production servers on increased PHP vulnerabilities through SQL Injection attacks, XSS (Cross Site-Scripting), Cookie hijack, miss configuration, social engineering, CSRF (cross site request forgery), OTP bypass (take over account) and others. Hacker attacks leave a backdoor or webshell that will be accessed remotely (remote), this is common in blackhat hackers. Provides a shelltrap framework to use for and perform and clean the backdoor on the server. Because the back door has characteristics, namely: (1) taking over the physical server or localrooting; (2) adaptation to the run time environment; (3) using global variables to access the server. Have evaluated shelltrap on realworld server tame PHP Script and PHP backdoor. The experimental results get high level detection results of 98 %.
The mediation effect of learning organization in the relationship between internal service quality and job satisfaction of nurses

AbstractBackground: There is little evidence about the influence of internal service quality on nurses’ job satisfaction and their ability to provide efficient patient care. This study aims to explore the mediating effect of ‘learning organization in the relationship between the internal service quality and job satisfaction of nurses in public hospitals in Cameroon.Methods: A total of 400 questionnaires were distributed to nurses in public hospitals between 20 February to 31 December 2017. The mediation analysis was conducted using SPSS and PROCESS model 4.Results: The impact of internal service quality and learning organization on the job satisfaction of nurses was significant and positive. In addition, learning organization fully mediates the relationship between internal service quality and job satisfaction.Conclusions: Internal service quality increases the job satisfaction of health workers via learning organization practice in public hospitals. Health care managers should be aware of factors that foster job satisfaction and provide a high quality of internal services that incorporate learning organization activities, to enhance existing medical skills and improve the job satisfaction of health workers for better health service delivery to patients. [Ethiop. J. Health Dev. 2020; 34(4):286-292]Key words: Nurses, internal service quality, learning organization, job satisfaction
NOUN PHRASE ANALYSIS OF MAGAZINE ARTICLE “VIDEO GAMES … ARE GOOD FOR YOU?” BY GABRIEL J. ADAMS

Understanding the text is one of the objectives of English study. Before understanding the complex sentence the basic skill that student need to master is to understand the phrases of each sentence. This article objectives are to give more understanding about noun phrases in magazine article to help student easy to understand the basic of English especially phrase. The reason writer choose noun phrase is the most commonly used phrase in the sentence is the noun phrase and the writer want to make the reader familiar with noun phrase. This article will analyze the magazine article with 22 sentences and also contains 66 noun phrases in it. Which the writer will determine the modifier every noun phrase in it. Therefore, mastering phrases is a key to become a fluent speaker of English. Keywords: Noun Phrases, Magazine Article
A Neural Network Approach to Writer’s Model for Full Likelihood Ratio in Handwriting Analysis

Handwriting is an integral part of our life that can predict who we are because the style of writing is unique for every person.Handwriting is also a key element in document examination as it leaves a forensic document examiner with the task of determining who the writer of a particular document is and this is achieved through the likelihood ratio (L R ) paradigm.Inability to model an individual's handwriting over time has made estimating a full likelihood ratio for comparative handwriting analysis impossible thereby employing nuisance parameters and subjectivity in computation of L R that is not full.This research employed back propagation neural network (BPNN) to model the writing pattern of individuals with input layer as the features of handwriting characters, two hidden layers of three neurons each, activation function sigmoid (s) and an output handwriting.With the help of handwriting model for individual writers, little or no assumptions and no nuisance parameters were employed in achieving full likelihood ratio for comparative handwriting analysis in forensic science.From the research carried out, it can be concluded that modeling an individual's handwriting is a crucial factor in achieving a full likelihood ratio, little/or no inconclusiveness in result reporting and a less degree of disagreements for handwriting identification in a forensic environment.
Context-Aware Target Apps Selection and Recommendation for Enhancing Personal Mobile Assistants

Users install many apps on their smartphones, raising issues related to information overload for users and resource management for devices. Moreover, the recent increase in the use of personal assistants has made mobile devices even more pervasive in users' lives. This paper addresses two research problems that are vital for developing effective personal mobile assistants: target apps selection and recommendation. The former is the key component of a unified mobile search system: a system that addresses the users' information needs for all the apps installed on their devices with a unified mode of access. The latter, instead, predicts the next apps that the users would want to launch. Here we focus on context-aware models to leverage the rich contextual information available to mobile devices. We design an in situ study to collect thousands of mobile queries enriched with mobile sensor data (now publicly available for research purposes). With the aid of this dataset, we study the user behavior in the context of these tasks and propose a family of context-aware neural models that take into account the sequential, temporal, and personal behavior of users. We study several state-of-the-art models and show that the proposed models significantly outperform the baselines.
Identification and Effective Summary Extraction with Deduplication of Data in News Articles

Text summary, which is the most prominent application for data pressure, is provided for natural language processing. Content rundown is a process for the summary of the unique archive measurement by reducing the number of vital data from a uniquely reported report. In less time, a need emerges that the development of information increases greatly on the World Wide Web or on desktops of customers so that the multi-document overview is the best way of summarising it in less time. This paper presents an examination of existing procedures with the odds of stressing the need for an intelligent multi-document resumer.
Guides: Subject Guide: Management and Marketing: Our Collections

A guide to getting the most out of the Library and Collections resources for Management and Marketing Databases for your subject
English Proficiency and Sequencing Skills in Narrative Writing of Public High School Students

This descriptive-comparative research explored the level of grammar proficiency and sequencing skills in narrative writing of the Grade 7 students. Specifically, it sought to determine the significant difference in the level of grammar proficiency and sequencing skills. The 308 Grade 7 students selected through stratified proportional sampling answered the researcher-made instrument. The findings revealed that the students have a low level of grammar proficiency and average level in sequencing skills as a whole. Moreover, a significant difference exists in the level of grammar proficiency and the level of sequencing skills of students when grouped according to academic performance in English and track, while no significant difference exists when the students are classified according to sex. The results imply that students can sequence events in a narrative. However, they find difficulty in writing grammatically correct sentences. With this, instructional materials may be designed to develop the students’ proficiency in writing.
Educación, conectividad y conectivismo: sus desafíos actuales

The contemporary era with the appearance of (ICTs) have posed new challenges to the teaching and learning processes and to the established pedagogical currents of behaviorism, constructivism and cognitivism. The computerization of the broadest fields of society, which encompasses all spheres of human performance, transcends the field of education and revolutionizes with new tools, the most orthodox pillars that have sustained it, it is in this framework that we are presented the need for discernment of what to understand by connectivity and connectivism beyond practice and theory itself, as the use of terminal tools with wide access to digital networks has its own challenges. The situation created in current Ecuadorian society, in the midst of developing the educational process telematically, exemplifies the contradictory nature of the analysis that is presented.
Development of the space-time structure of the methodology for modeling the behavior of antagonistic agents of the security system

The rapid development of computer technology, the emergence of modern cyber threats with signs of hybridity and synergy put forward strict requirements for the economic component of national security and especially the processes of ensuring the economy cybersecurity. The cybersecurity industry is trying to meet today's requirements by introducing new and more advanced security technologies and methods, but it is believed that such a universal approach is not enough. The study is devoted to resolving the objective contradiction between the growing practical requirements for an appropriate level of cybersecurity of business process contours while increasing the number and technological complexity of cybersecurity threats. Also the fact that threats acquire hybrid features on the one hand, and imperfection, and sometimes the lack of methodology for modeling the behavior of interacting agents of security systems should be taken into account. However, this does not allow timely prediction of future actions of attackers, and as a result, determining the required level of investment in security, which will provide the required level of cybersecurity.The paper proposes the Concept of modeling the behavior of interacting agents, the basis of which is a three-level structure of modeling the subjects and business processes of the contours of the organization and security system, based on modeling the behavior of antagonistic agents. The proposed methodology for modeling the behavior of interacting agents, which is based on the Concept of behavior of antagonistic agents, allows assessing and increasing the current level of security by reducing the number of hybrid threats by 1.76 times, which reduces losses by 1.65 times and increases the time for choosing threat counteraction means by reducing the time to identify threats online by 38 %
Multi-Model Least Squares-Based Recomputation Framework for Large Data Analysis

Most multilayer least squares (LS)-based neural networks are structured with two separate stages: unsupervised feature encoding and supervised pattern classification. Once the unsupervised learning is finished, the latent encoding would be fixed without supervised fine-tuning. However, in complex tasks such as handling the ImageNet dataset, there are often many more clues that can be directly encoded, while the unsupervised learning, by definition cannot know exactly what is useful for a certain task. This serves as the motivation to retrain the latent space representations to learn some clues that unsupervised learning has not yet learned. In particular, the error matrix from the output layer is pulled back to each hidden layer, and the parameters of the hidden layer are recalculated with Moore-Penrose (MP) inverse for more generalized representations. In this paper, a recomputation-based multilayer network using MP inverse (RML-MP) is developed. A sparse RML-MP (SRML-MP) model to boost the performance of RML-MP is then proposed. The experimental results with varying training samples (from 3 K to 1.8 M) show that the proposed models provide better generalization performance than most representation learning algorithms.
Nonlinearities on particular elliptic curves subspaces and applications

Abstract Researching on mathematical models for cryptography means to, primary, define the optimal spaces and rules for which we can archive the maximum time to find the involved parameters of the keys and, in the same time, to optimise the time for key generation. In the present work, we treat a particular case of some subspaces from elliptic curves which respect the announced principles.
Comparative Study of Density-based Clustering Algorithms

Data mining and exploratory data analysis deal with large datasets wherein one of the objective isto group objects such that objects falling under the same group have more similarities than the objects of twodifferent groups, these groups are called clusters. Here similarity of objects is measured in terms of distancebetween the objects. The process of grouping objects is called clustering. There are numerous applications ofclustering in variety of fields and data involved in each varies a lot. This has led researchers to come out withvarious methods and models of clustering. There are different types of clustering methods: Hierarchical,Partitioning, Density Based, Grid based and Graph Based. This paper presents a study of various methods ofclustering and discusses briefly on various Density based clustering methods.
Economic Study of the Use of Renewable Energy and Technology in Growing Summer Tomatoes

The agricultural sector occupies an important place among the sectors of the national economy, so we must increase the average yield per acre of agricultural crops, more than By using what was developed in the field of modern technology, so renewable energy and technology is the most appropriate in all these current Egyptian economic changes.Where the production functions using the log-stage model show that the production of the summer tomato crop using solar irrigation during the season 2019, that the model used as a whole is significant at the probability level (0.01), where it was found that there is a statistically positive relationship between the quantity of production (r) per ton, and each of the total Human labor (Q1), total automatic working hours per hour / feddan (Q2), the amount of nitrogen fertilizer per unit (Q5), the amount of potassium fertilizer per unit (Q7), as by increasing the previously mentioned independent factors by 1%, it leads to an increase in summer tomato production by about 0.328%, 0.320%, 0.595%, 0.45%, respectively, as the staged logarithmic model shows that Equation No. (2) In Table No. (2) The effect of the aforementioned variables on the yield of the summer tomato crop using solar irrigation during the season 2019, that the model used As a whole meaning at the probability level (0.01), where it was found that there is a statistically positive relationship between the quantity of production (y) per ton, and each of the total automatic working hours hour / feddan (Q2), the amount of municipal fertilizer (Q4), and the amount of potassium fertilizer per unit (Q7) As it is by increasing the factors A. The aforementioned independent one by 1% would lead to an increase in summer tomato production by about 0.746%, 0.119% and 0.879%, respectively.Where it became evident that the farmers who used solar energy irrigation achieved the highest net return of the summer tomato crop, which amounted to about 33.85 thousand pounds, while the irrigation farmers who used solar irrigation achieved the lowest net return of the tomato crop, which amounted to about 11.97 thousand pounds.
STRATEGY IMPROVES THE NUMBER OF NEW STUDENTS IN SEKOLAH MENENGAH ATAS NEGERI 1 GETASAN THROUGH ISHIKAWA DIAGRAM APPROACH (FISHBONE)

The purpose of this study is to identify the factors that influence the interests of prospective students to register at Sekolah Menengah Atas (SMA) Negeri 1 Getasan. The technique used in this research is to analyze and process the data based on Ishikawa diagram techniques. The results of this study were to determine the strategies that were formulated including: (1) Implementing additional learning and tutoring for students who have prominent academic potential;(2) Developing a local curriculum on entrepreneurship related to food processing subjects such as making geplak waluh; (3) Completing classroom facilities; (4) Optimizing Multimedia and Computer laboratories by organizing their use for Junior High School that do not yet have facilities; (5) Enacting policies that take into account the economic capabilities of surrounding communities for children who attend SMA Negeri 1 Getasan; (6) Implementing policies by considering cross-subsidies especially for students whose parents come from the environment around the school; (7) Establishing better cooperation with the community around the school, especially with regard to certain events; and (8) Scheduling activities targeting junior high school students such as the Festival Band for junior high school or holding an open house on high school anniversaries.
Document-aligned Japanese-English Conversation Parallel Corpus

Sentence-level (SL) machine translation (MT) has reached acceptable quality for many high-resourced languages, but not document-level (DL) MT, which is difficult to 1) train with little amount of DL data; and 2) evaluate, as the main methods and data sets focus on SL evaluation. To address the first issue, we present a document-aligned Japanese-English conversation corpus, including balanced, high-quality business conversation data for tuning and testing. As for the second issue, we manually identify the main areas where SL MT fails to produce adequate translations in lack of context. We then create an evaluation set where these phenomena are annotated to alleviate automatic evaluation of DL systems. We train MT models using our corpus to demonstrate how using context leads to improvements.