Reviewerly/exHarmony huggingface dataset:
Artificial neural networks for 3D cell shape recognition from confocal images

We present a dual-stage neural network architecture for analyzing fine shape details from microscopy recordings in 3D. The system, tested on red blood cells, uses training data from both healthy donors and patients with a congenital blood disease. Characteristic shape features are revealed from the spherical harmonics spectrum of each cell and are automatically processed to create a reproducible and unbiased shape recognition and classification for diagnostic and theragnostic use.
Academician S.L. Soloviev 90th birthday (1930–1994)

April 12, 2020, marks the 90th anniversary of the birth of the outstanding Soviet and Russian geophysicist Sergey L. Soloviev. He is the founder of the Russian school of tsunami research and made a significant contribution to the development of Russian seismology.
A Detailed Look At CNN-based Approaches In Facial Landmark Detection

Facial landmark detection has been studied over decades. Numerous neural network (NN)-based approaches have been proposed for detecting landmarks, especially the convolutional neural network (CNN)-based approaches. In general, CNN-based approaches can be divided into regression and heatmap approaches. However, no research systematically studies the characteristics of different approaches. In this paper, we investigate both CNN-based approaches, generalize their advantages and disadvantages, and introduce a variation of the heatmap approach, a pixel-wise classification (PWC) model. To the best of our knowledge, using the PWC model to detect facial landmarks have not been comprehensively studied. We further design a hybrid loss function and a discrimination network for strengthening the landmarks' interrelationship implied in the PWC model to improve the detection accuracy without modifying the original model architecture. Six common facial landmark datasets, AFW, Helen, LFPW, 300-W, IBUG, and COFW are adopted to train or evaluate our model. A comprehensive evaluation is conducted and the result shows that the proposed model outperforms other models in all tested datasets.
The Effectiveness of BIPA Learning at Students of Indonesian Concentration Department, Fatoni University, Thailand

This study aims to describe the effectiveness of learning Indonesian for Foreign Speakers (BIPA) at students of Indonesian Concentration Department, Fatoni University.The subjects of the study were the students of Indonesian Concentration Department.The data of this research were collected through questionnaire and test.The results showed that BIPA learning could be more effective in learning Indonesian in general.This could be proven from the questionnaire and tests taken by the students in which on speaking tests, students were better in communicating Indonesian; and in reading test, the students show increasingly in understanding text.The students also showed more capability in the making paragraph on the writing test as well as in listening test in which the students were able to understand fully what were said on the test.The research also noted that both students of Malay and Thai mother tongue /first language had better ability of those four skills of Indonesian.Meanwhile, the students who used to lived in Indonesia and Malaysia showed excellent skill in speaking and reading, while in writing and listening skill were categorised good.
Local Wisdom in Learning Materials of Indonesian for Foreign Speaker at Sebelas Maret University

Indonesian Language can be a symbol of national identity and the tool to unify people with different social, cultural, religion, and vernacular background.Besides, Indonesian Language functions as a modern communication medium in conducting the government, education, and science development.Nowadays, Indonesian Language becomes one of important languages in the world through the program of BIPA (Bahasa Indonesia for Foreign Speaker).This study aims to find out the local wisdom in the learning material of BIPA UNS.Descriptive qualitative is used for the methodology with the approach of local wisdom.Data collection is done through document analysis and in-depth interview.Repeated reading and context focusing on the local content material is done to analysis the data.The results showed that BIPA learning material contains the cultural aspect of local content and the language of communication used in the learning material is Indonesian Language.
Study of the Pattern Recognition Algorithms for the Automation of a Smart Semaphore Through FPGAs

The following document presents the development of an intelligent traffic light, based on FPGA technology, which assessing the amount of traffic gives priority to the lane with the highest number of cars. The comparative study of pattern recognition algorithms was performed: color matching algorithm, cross correlation algorithm and optical character recognition algorithm (OCR). The methodology for the development of the system is based on a matrix of programmable logic gates in the field or FPGA, a camera that acquires images and sends them for digital processing programmed in LabView intelligently with pattern recognition algorithms for decision making in the area of vehicular traffic control. The density of vehicular traffic is determined and the card changes the duration of the green light given for each lane according to the number of existing vehicles. As a result, it was obtained that the most appropriate algorithm to implement an intelligent traffic light prototype using FPGAs was the color matching algorithm that has an accuracy of 100% and a response time of 3 ms.
PREDICTION OF DESIGN ASPECTS OF WEB PAGE BY HTML PARSER

Inform plays a very important role in life and nowadays, the world largely depends on the World Wide Web to obtain any information. Web comprises of a lot of websites of every discipline, whereas websites consists of web pages which are interlinked with each other with the help of hyperlinks. The success of a website largely depends on the design aspects of the web pages. Researchers have done a lot of work to appraise the web pages quantitatively. Keeping in mind the importance of the design aspects of a web page, this paper aims at the design of an automated evaluation tool which evaluate the aspects for any web page. The tool takes the HTML code of the web page as input, and then it extracts and checks the HTML tags for the uniformity. The tool comprises of normalized modules which quantify the measures of design aspects. For realization, the tool has been applied on four web pages of distinct sites and design aspects have been reported for comparison. The tool will have various advantages for web developers who can predict the design quality of web pages and enhance it before and after implementation of website without user interaction.
Building a Hebrew Semantic Role Labeling Lexical Resource from Parallel Movie Subtitles

We present a semantic role labeling resource for Hebrew built semi-automatically through annotation projection from English. This corpus is derived from the multilingual OpenSubtitles dataset and includes short informal sentences, for which reliable linguistic annotations have been computed. We provide a fully annotated version of the data including morphological analysis, dependency syntax and semantic role labeling in both FrameNet and PropBank styles. Sentences are aligned between English and Hebrew, both sides include full annotations and the explicit mapping from the English arguments to the Hebrew ones. We train a neural SRL model on this Hebrew resource exploiting the pre-trained multilingual BERT transformer model, and provide the first available baseline model for Hebrew SRL as a reference point. The code we provide is generic and can be adapted to other languages to bootstrap SRL resources.
RESEARCH ON THE DEVELOPMENT OF PROFESSIONAL NAVIGATIONAL COMPETENCE OF FUTURE SHIP NAVIGATORS BY MIXED REALITY SIMULATION TECHNOLOGIES

The monograph presents European and regional development trends in innovative scientific researches in pedagogical sciences. The general issues of the history of pedagogy, theory and methodology of teaching, correctional pedagogy, theory and methodology of vocational education and management of education, information and communication technologies in education, etc. are considered. The publication is intended for scholars, teachers, postgraduate students, and students of pedagogical specialties, as well as a wide readership interested in pedagogy. Innovative scientific researches: European development trends and regional aspect. Collective monograph. – 1st ed. – Riga, Latvia : “Baltija Publishing”, 2020. – 492 p.
Hardware Implementation of Adaptive Watermarking Based on Local Spatial Disorder Analysis

With the increasing use of the internet and the ease of exchange of multimedia content, the protection of ownership rights has become a significant concern. Watermarking is an efficient means for this purpose. In many applications, real-time watermarking is required, which demands hardware implementation of low complexity and robust algorithm. In this paper, an adaptive watermarking is presented, which uses embedding in different bit-planes to achieve transparency and robustness. Local disorder of pixels is analyzed to control the strength of the watermark. A new low complexity method for disorder analysis is proposed, and its hardware implantation is presented. An embedding method is proposed, which causes lower degradation in the watermarked image. Also, the performance of proposed watermarking architecture is improved by a pipe-line structure and is tested on an FPGA device. Results show that the algorithm produces transparent and robust watermarked images. The synthesis report from FPGA implementation illustrates a low complexity hardware structure.
The Students’ Difficulties In Pronouncing The English Vowels At The Seventh Grade Of SMPN 2 Simo In 2017/2018 Academic Year

The purpose of this research is aimed to describe what vowel sounds are difficult to pronounce by the students and what factors that cause difficulties in pronouncing the English vowels at the seventh grade of SMP N 2 Simo. This research is descriptive qualitative research. The subject of this research was the seventh grade students of SMPN 2 Simo in 2018/2019 academic year namely class 7A that consisted of 30 students. The data in this research were obtained from pronunciation test and interview. The result showed that the students of SMPN 2 SIMO got some English vowel difficult to pronounce. The English vowel sounds which are difficult to pronounce by the students are [ae], [ə], [ɜː]. And the diphthong sounds difficult to pronounce by the students are [eɪ], [aɪ] and [ɔɪ]. The factors that cause difficulties in pronouncing English vowels are: 1) Native language interference, 2) Students’ low motivation in learning English, 3) Infrequent of pronunciation lesson, 4) Unconducive learning atmosphere
Infinite mixtures of multivariate normal-inverse Gaussian distributions for clustering of skewed data

Mixtures of multivariate normal inverse Gaussian (MNIG) distributions can be used to cluster data that exhibit features such as skewness and heavy tails. However, for cluster analysis, using a traditional finite mixture model framework, either the number of components needs to be known $a$-$priori$ or needs to be estimated $a$-$posteriori$ using some model selection criterion after deriving results for a range of possible number of components. However, different model selection criteria can sometimes result in different number of components yielding uncertainty. Here, an infinite mixture model framework, also known as Dirichlet process mixture model, is proposed for the mixtures of MNIG distributions. This Dirichlet process mixture model approach allows the number of components to grow or decay freely from 1 to $\infty$ (in practice from 1 to $N$) and the number of components is inferred along with the parameter estimates in a Bayesian framework thus alleviating the need for model selection criteria. We provide real data applications with benchmark datasets as well as a small simulation experiment to compare with other existing models. The proposed method provides competitive clustering results to other clustering approaches for both simulation and real data and parameter recovery are illustrated using simulation studies.
ReadNet: Towards Accurate ReID with Limited and Noisy Samples.

Person re-identification (ReID) is an essential cross-camera retrieval task to identify pedestrians. However, the photo number of each pedestrian usually differs drastically, and thus the data limitation and imbalance problem hinders the prediction accuracy greatly. Additionally, in real-world applications, pedestrian images are captured by different surveillance cameras, so the noisy camera related information, such as the lights, perspectives and resolutions, result in inevitable domain gaps for ReID algorithms. These challenges bring difficulties to current deep learning methods with triplet loss for coping with such problems. To address these challenges, this paper proposes ReadNet, an adversarial camera network (ACN) with an angular triplet loss (ATL). In detail, ATL focuses on learning the angular distance among different identities to mitigate the effect of data imbalance, and guarantees a linear decision boundary as well, while ACN takes the camera discriminator as a game opponent of feature extractor to filter camera related information to bridge the multi-camera gaps. ReadNet is designed to be flexible so that either ATL or ACN can be deployed independently or simultaneously. The experiment results on various benchmark datasets have shown that ReadNet can deliver better prediction performance than current state-of-the-art methods.
The Effect of MYOB Test Clinic Toward Student Competence

The objective of this study to prove the effect of the implementation of MYOB test clinic on improving student competence in the D4 (Diploma) Public Accounting Study Program. The data used in this study are primary data obtained from questionnaires. Respondents of this study were 52 students of D4 Accounting Public Accounting Study Program. The data analysis method used is multiple regression statistical analysis. Based on the evaluation results of the MYOB test clinic, the average value obtained increased from 48 before to 74 or an increase of 52%. The results showed that the method variables, material, and instructor of MYOB test clinic had no effect on the competence of students in the D4 Public Financial Accounting Study Program. The contribution of MYOB test clinic's method, material, and instructor variables on student competence is only 1.9% and the remaining 98.1% is influenced by other variables.
Clustering Potensi Susu Sapi Perah Di Kabupaten Boyolali Menggunakan Algoritma K-MeansK-MEANS

Based on data of dairy milk cow in Animal Farms of Boyolali District, only shows the total amount of dairy milk cow in Boyolali District. So that Animal Farms of Boyolali District does not know which areas produce dairy milk cows with large numbers or small. Therefore, an algorithm is needed to facilitate the grouping of potentially dairy milk cow based on milk production data (liter), number of female dairy cows (how many), number of owners and year of production. In this research, using the K-Means algorithm is used to the grouping of potential dairy milk cow producing areas. By using K-Means aims in facilitating the classification of an area that has the greatest potential dairy milk cows, medium and small. The result is an illustration that shows the regional grouping based on dairy milk cow yields, which are 13 districts that have a potency of dairy milk cow (cluster1), 28 districts that have medium potency dairy cows producing (cluster2), and 28 districts less potential dairy milk cows (cluster3). For further research could be carried out the excavation process variation data variables that clustering results produced can be maximized.Keywords: K-Means algorithm, clustering, data mining, dairy milk cows
Facial Expression Recognition Using Deep Convolution Neural Network With Tensorflow

Facial expression recognition (FER) is an automatic system that manipulates the facial data and plays a vital role in human machine interfaces. Olden machine learning algorithms has attracted incrementing attention from researchers since the early nineties. It approaches often requires complex feature extraction process. In this paper we reflected recent advances in deep learning to Convolutional Neural Networks (CNN). It is an prominent field which uses nowadays applications such as in robots, games and neuromarketing. It is widely used technique uses facial expressions, eye movement and gestures which conveys the emotional status and feelings of persons. The proposed model made pivot on detecting the facial expressions of an individual from a single image. The number of parameters in our proposed networks concentrated by decreasing manner that accelerates the total performance speed and makes this well and make suitable for real time systems
Socio-behavioral elements in data-driven requirements engineering: The case of enterprise cloud software

The ongoing transition from on-premise to cloud solutions in the enterprise software market entails important changes in how software vendors interact with their users. Where user involvement has traditionally been a challenge, increasingly large amounts of usage and feedback data now allow for datadriven requirements engineering (RE). Prior research has provided conceptualizations of data-driven RE, introduced initial technical prototypes, and shed light on the general social interactions in RE. However, extant research lacks a comprehensive perspective on the socio-behavioral elements of datadriven RE for enterprise cloud software development and empirical insights. We obtained access to a large enterprise cloud software vendor for a revelatory single-case study and conducted interviews within seven different cloud software products. We demonstrate how data-driven RE affects knowledge transfer, mental models, and trust between stakeholders. We observe a shift from a stakeholder-centric towards a more user-centric RE process by opening new direct requirements elicitation channels between the users of a software and the development organization. Our study reveals that the data-driven approach holds much potential to scale and accelerate RE for enterprise cloud software, but there are still numerous obstacles to overcome in order to achieve high levels of context-awareness, continuity, and automation in RE.
History of “Anthropocentrism” Notion in the Context of Modern Thinking on Man and Civilisation

The aim of the study is determined by an attempt to analyse the main discursive patterns in the history of the anthropocentric idea, which are interpreted in inextricable connection to the capability of describing modern perceptions of the world and a man. The article provides various interpretations of the anthropocentrism notion as one of philosophical conceptions throughout differrent historical periods, from the ancient times to modern scientific inquires in the context of the most topical issues. The study is novel in that it substantiates potentiality of treating the concept of anthropocentrism as a crucial marker of the philosophical thought development throughout all the stages of human history, a marker representative of a man’s universal reflection regarding his standing in the world and axiological attitudes. The attained results make it possible to embark upon analysing general as well as specific cognitive interests and preferences presented in different branches of modern scientific knowledge, in the context of cognitions characterising the discourse of the anthropocentric idea.
The Massive Development of Web-Based Office Applications

The development of information and communication technology is no longer unstoppable because of the demands it demands.The use of information and communication technology goes into all fields of service and goods industries.The internet has become a trigger of developments in information and communication technology.Just ask an office application that utilizes the internet to connect one office with another office.Website technology allows applications to be opened on all kinds of hardware platforms such as computers, handheld computers, tablets, and smartphones.Due to the development of hardware in computers, this also changed the basis of office applications.Office applications will be more flexible if they are based on a website because they can be opened quickly from any hardware platform with only a browser and internet connection.The massive development of Website-based office applications is indeed a need to increase the effectiveness and efficiency of a company's production process.This office application will continue to experience developments that adjust to the industrial revolution of 4.0 and the next generation.
Text-Based BIPA Teaching in Industrial Revolution Era 4.0

This article is a text-based BIPA (Indonesian for Foreigner Learner) teaching idea in the industrial revolution era 4.0.Teaching BIPA in the era of the industrial revolution 4.0 presents its own challenges for teachers and learners.Texts in the industrial revolution era circulated in various modes, not only language modes, but also visual and audio modes based on big data.Teaching BIPA text-based material in 4.0 era means making text 4.0 as a means of mastering the learner's language competence.Stages of BIPA teaching model based on text 4.0 are (1) building the context of the text; (2) deconstructing the context of the text; (3) gradually training students; and (4) independent performance.To balance out the competence in using technological sophistication, BIPA teachers must still have basic skills in mastering (1) SKL (graduate competence standard) BIPA learning that can refer to the contents of Permedikbud Num.27/2017; (2) basic principles of BIPA learning; (3) Indonesian language discipline content; (3) various teaching methodologies, especially for teaching foreign languages or second languages; andragogy teaching concepts; and the concepts of teaching planning, implementation and evaluation.
INFORMATION TECHNOLOGY OF PROBLEMS SOLUTIONS SUPPORT IN A COMPLEX SYSTEM MANAGEMENT

The study of the problems arising in the management of complex multi-factor systems allows to conclude that the latter should be considered as integrated organizational and technical. The basis of such management is a crisis – an exciting phenomenon, an incentive – unfulfilled needs, a defect, a deficiency or a threat that causes a targeted crisis through technical intervention or to avoid interaction or a change in the state of an object, a change in oneself or one's attitude to what is happening. An information technology for overcoming crises is proposed, which consists in the construction of each crisis into a group of elementary ones with the subsequent transformation of each elementary crisis into an elementary solution using the proposed information technology. The aim of research is to increase the efficiency of managing the development of complex organizational and technical systems through the development and implementation of new dynamic models and methods for finding optimal ways to overcome management crises at the level of elementary representations. The analysis and classification of the negative circumstances that arise in the management of complex dynamic organizational and technical systems, and the crises arising from these circumstances are carried out. The life cycle of an elementary crisis in managing the development of complex organizational and technical systems is shown – from the emergence of elementary negative circumstances to the receipt of elementary solutions to overcome them. An informational method has been developed to support decision making on the choice of means to overcome crises, based on the use of multidimensional percolation models. The structure is proposed and a description of the main steps that are carried out at one iteration of managing a complex organizational and technical system is provided