Reviewerly/exHarmony huggingface dataset:
Securing Big Data-Based Smart Applications Using Blockchain Technology

Nowadays, Big Data is the most salient paradigm. It has become a game-changer in the current technology and has aroused various industries and research communities worldwide. Big Data-based applications have shown much potential in data-driven decisions that have changed all business operations, including cost optimization, online reputation, and customer loyalty. Nevertheless, Big Data also brings many security and privacy issues. For this reason, Big Data applications require accurate methods to ensure reliable data storage, sharing, and decision-making. Among these methods, the Blockchain is known as the clever combination of distributed exchange, consensus, and cryptography mechanisms. It has been brought to the forefront to resolve security challenges in various fields such as Healthcare, banking, smart cities, etc. This paper first presents the considerable difficulties faced when adopting Big Data that can be resolved using Blockchain. Afterward, we overview the Blockchain technology by projecting its components, workflows, classification, and related characteristics. Finally, we present the importance of combining Big Data and Blockchain through reviewing the novel implementations proposed by researchers in great domains.
Multiphasic array radar target assignment algorithm based on improved Hopfield Neural Network

The problem of target allocation should be considered when the multi-target tracking is realized by multi-phased array radar. In this paper, an algorithm for target allocation of multi-phased array radar based on improved Hopfield neural network is proposed to improve the time utilization rate of radar and the possibility of tracking high-priority targets under the circumstance of time resource limitation. In this paper, a mathematical model of target allocation for multiphasic array radar is established, which takes the sum of time utilization and target priority as the objective function and radar time resource as the constraint condition. Secondly, the improved Hopfield neural network is introduced. This neural network alleviates the shortcoming of the common Hopfield neural network that is prone to fall into local optimal, and it is used for model solving. Finally, the simulation results show that the algorithm is effective.
Boundary-Aware Dual Attention Guided Liver Segment Segmentation Model

Accurate liver segment segmentation based on radiological images is indispensable for the preoperative analysis of liver tumor resection surgery.However, most of the existing segmentation methods are not feasible to be used directly for this task due to the challenge of exact edge prediction with some tiny and slender vessels as its clinical segmentation criterion.To address this problem, we propose a novel deep learning based segmentation model, called Boundary-Aware Dual Attention Liver Segment Segmentation Model (BADA).This model can improve the segmentation accuracy of liver segments with enhancing the edges including the vessels serving as segment boundaries.In our model, the dual gated attention is proposed, which composes of a spatial attention module and a semantic attention module.The spatial attention module enhances the weights of key edge regions by concerning about the salient intensity changes, while the semantic attention amplifies the contribution of filters that can extract more discriminative feature information by weighting the significant convolution channels.Simultaneously, we build a dataset of liver segments including 59 clinic cases with dynamically contrast enhanced MRI(Magnetic Resonance Imaging) of portal vein stage, which annotated by several professional radiologists.Comparing with several state-of-the-art methods and baseline segmentation methods, we achieve the best results on this clinic liver segment segmentation dataset, where Mean Dice, Mean Sensitivity and Mean Positive Predicted Value reach 89.01%, 87.71% and 90.67%, respectively.
Risk And Return Model of Digital Cryptocurrency Asset Investment In Indonesia

&lt;p&gt;&lt;em&gt;Cryptocurrency is an investment commodity that can generate returns and already has a license to be traded in exchange trading through the Indonesian Commodity Futures Trading Regulatory Agency (BAPEPTI). There are quite a lot of crypto digital assets traded in Indonesia through the trading company Indodax. The purpose of this research is focused on formulating a risk management process in cryptocurrency digital asset investment. In addition, from the results of this study, a policy recommendation known as LCTR or "Legal Cryptocurrency and Tax Revenue" is expected to be considered by the government in formulating policies on crypto digital assets so that the interests of all parties can be accommodated for the realization of maximum state revenue from commodity trading. crypto digital assets. This type of research is quantitative descriptive with the research population, namely 5 cryptocurrency coins with the largest market caps in Indonesia, namely Bitcoin, Ethereum, Ripple, Bitcoin Cash, Litecoin in Indonesia. The type of data in this study is time series data taken from March 2021 to December 2021 by conducting a documentation study conducted on the publication of monthly cryptocurrency transaction reports, so that a target population of 240 (4 years x 12 months x 5 coins) monthly report data is obtained. for the research sample. The data analysis method in this study used multiple linear regression and data analysis used statistical software e-views version 10. The output of this study was the publication of reputable international journals,&lt;/em&gt;&lt;em&gt;&lt;/em&gt;&lt;/p&gt;&lt;p&gt; &lt;/p&gt;
Machine and federated learning for high-performance computing: a survey

A paradigm shift in machine learning (ML) application models has occurred in the preceding years due to privacy and deep learning aspirations. The recently created decentralised paradigm of ML is known as federated learning. Federated learning (FL) is a ML technique in which many dispersed nodes use their locally stored data to train a common prediction model. Better data privacy is possible because the training data is not routed to a central server. FL offloads the processed information to the server and does not need clients to share their personal information. However, FL is a new field that has yet to achieve mainstream acceptance and is still in the development phase. In this context, the purpose of our study is to provide a more comprehensive overview of the most important protocols, platforms, and real-world FL use cases, which will allow researchers to develop privacy-preserving solutions for businesses that require FL.
Clustered adaptive neuro-fuzzy inference system models of net radiation flux using temperature series

This study proposes three clustered adaptive neuro-fuzzy inference system (ANFIS) models for the prediction of net radiation flux over climatic regions in Nigeria. Five temperature indices data obtained from the Nigerian Meteorological Agency, Lagos covering a period 1983 to 2013 were used as input variables to train and test the ANFIS models. Comparative analyses of the three ANFIS models—grid partitioning clustering (GPC), the subtractive clustering (SC), and the fuzzy c-means clustering (FCM) using the minimum values of coefficient of uncertainty (UII)—showed that ANFIS-GPC performed best in the semi-arid and sub-humid humid regions with values of 0.089 and 0.092, respectively. ANFIS-FCM performed best in the sub-humid dry region with a value of 0.074. ANFIS-SC performed best in the humid region with a value of 0.080. It can be concluded that the proposed models are regional dependent, and they are suitable for the prediction of net radiation flux over respective tropical regions for practical purposes.
Formation technologies of professional competence for prospective teachers

The organizational and atavistic block of research competencies is characterized by the criterion of acquiring skills to organize research activities by a teacher. Thus, this study attempts to analyze the formation technologies of professional competence for prospective teachers. To attain the aim of the study, a descriptive method is utilized. The studies of the process of managing the psychological and pedagogical competencies of a higher education teacher are taken into account to come to a reliable conclusion. Based on the results obtained, it can be concluded that there is a necessity for the proper organization of activities and the active use of technology for working with students and young people, which makes it possible to combine teaching and educational goals as much as possible, both in the educational process and beyond.
Development, Implementation and Evaluation of E-Teaching Certificates

AbstractProfessors and lecturers in higher education who are used to teaching in physical face-to-face situations often take a critical stance towards online education formats. This is due to a lack of digital teaching experience and—especially in Germany—a digital-critic mindset. One key approach to overcome these uncertainties is to implement training programs that address digital teaching competency, reduce (mindset) barriers, offer comprehensive support regarding basic technical issues, and provide opportunities to apply the newly acquired digital teaching skills in a fail-safe setting. This paper details (1) how an evidence-based faculty development program as well as a virtual teaching setting for professors and lecturers was designed, (2) how they were implemented and what challenges were addressed during the process of the program implementation, and (3) what mid- and long-term effects were discovered in a follow-up evaluation.
Development of an Open Digital Platform “Digital PsyTech” for Psychological and Pedagogical Support of Participants in the Educational Process

The article discusses the experience of developing and implementing an open digital platform “Digital PsyTech” for the psychological and pedagogical support of the participants in the educational process on the basis of a multidisciplinary university. Along with the functions of socialization, reproduction and development of corporate culture, great importance is paid to the socio-psychological aspect of the development of the future specialist and the reduction of stress in the teaching and management team. The psychological platform for distance learning and development of participants in the educational process of Peter the Great St. Petersburg Polytechnic University (SPbPU) is based on the methods of psychological work and combines the experience of world web services, Russian and authors’ developments in the field of distance counseling. The format involves individual and group work, conducting online seminars on the most relevant issues with built-in training modules in the field of psychology of self-knowledge, self-development, self-assistance, organizing online consultations, and implementing educational programs. The multi-component structure of the psychological platform tools for distance learning and development of participants in the educational process of SPbPU “Digital PsyTech” is presented, which includes two modules: Digital Channels (DC), Digital Technologies (DT). The digital help, training and development button is developed, and the possibilities of the effective use of distance psychological and pedagogical technologies in the face of big challenges are described.
ANALYSIS OF THE COMPETENCE-BASED APPROACH OF THE SCHOOLS’ CURRICULUM OF THE REPUBLIC OF KAZAKHSTAN: DIGITAL COMPETENCES

This article presents a qualitative analysis of the content of educational curricula for the presence of elements of a competency-based approach with an emphasis on the development of digital competence of students. As an object of study, educational programs and mid-term plans of senior classes in the subjects of computer science (as a specific subject) and mathematics (as a general education subject), implemented in schools of the Republic of Kazakhstan in the 2020-2021 academic year, were chosen. The results of the analysis show the need to develop a digital competence framework for high school students, which could specify the types and components of digital competence and become a guideline for planned revisions of the content of educational programs in high school.
A Sequent Calculus

An analysis of mathematical proofs leads to the notion of formal proof. Formal proofs are obtained by applying the rules of a calculus consisting of purely formal operations on formulas of first-order logic. An example illustrates how a standard mathematical proof is converted to a formal proof.
A Study on the Development of Design thinking in the Fourth Industrial Revolution — Focused on Micro Manufacturing Space

Recent advances in technology have accelerated the Fourth Industrial Revolution. With the emergence of artificial intelligence, not only the manufacturing sector but also all sectors of society are expected to undergo changes in the future. In this age of the Fourth Industrial Revolution, it is going to be more important for learners to improve their creativity than to acquire knowledge. So scholars are exploring new ways of teaching to cultivate suitable talent for the future society. Among these various methods of education, Maker Education at Micro Manufacturing Space is recognized as the optimal method for the AI era. This study, in light of this, analyzed the operation of Micro Manufacturing Space, which is located in a university, and further suggested the direction of development of Micro Manufacturing Space in the Fourth Industrial Revolution. The results of this study are as follows. At the university’s Micro Manufacturing Space, students can be trained to think innovatively and improve creativity. In addition, this space can also be used as an open learning and meeting space for university students to visit freely. Moreover, the place can be built for the purpose of a start-up space. Therefore, future Micro Manufacturing Space in universities, as it were, will definitely prove to be a multifunctional space providing support to foster and improve creativity of the main force of the future of society. The findings can be used as theoretical basic data in the creation of a Micro Manufacturing Space for design thingking.
Blockchain-based Ubiquitous Learning Method towards Higher Education security

In the last fifteen years, the acceleration of technology and information has been accelerating from year to year. Along with the ongoing digitalization, which brings different problems, issues that often arise regarding the preparation of the current workforce are moving towards further education. In this preparation, pragmatic and hypothetical information can emerge from various containers, mean and channels, whether formal or causal. In addition, it is very difficult to evaluate the level of information skills that students acquire in order to increase their chances of finding jobs in the future. This, along with the need to oversee general education programs, the issue of certainty when approving these files and distinguishing them from original information, and so on, implies that administration in further education needs new, progressive instruments. This work assesses the advantages of blockchain innovation (or delivered notes) and supports a decentralized certainty model for blockchain ubiquitous deployments. In this methodology, blockchain is used to oversee transactions of substance, education and abilities, evaluated with the approval of students, mentors and businesses, to remove for the last time the "gap" between academia and the world of work. This paper intends to address the pervasive, open and ubiquitous current challenges of continuing education. The proposed model can be implemented in any preparatory organization to tailor instructions to the specific needs of an expert profile approved by superiors at the second summit. This model is approved by the method for models with results that more than just acknowledge.
Prediksi Harga Saham Menggunakan BiLSTM dengan Faktor Sentimen Publik

Stock market is one economic driver. It has roles in growth and development of a country. Stock is an attractive investment due to the huge profit. Many people buy and sell their stock. Stock investors try to choose the good investment company to get profits with small risk. Therefore, stock investors need to be careful and must evaluate a company. With machine learning technology, stock prediction problems can be solved. Deep learning is a subset of machine learning with own network. Deep learning has good performance in managing large amounts of data. This study used stock price history data and public sentiment data on a company. The method used in this research is Bidirectional Long-Short Term Memory (BiLSTM). The features used were closing price and compound score value of the public sentiment. Four scenarios were used in finding the best predictive model. The four scenarios use the same test data with different lengths of training data window. From the modelling, predictions with the model built using BiLSTM resulted in the smallest MSE value of 0.094 and the smallest RMSE value of 0.306.&#x0D;
MRS. WELLINGTON'S ANXIETY IN GITTY DANESHVARI'S SCHOOL OF FEAR: THE FINAL EXAM

This study is entitled Mrs. Wellington’s anxiety reflected in Gitty Daneshvari’s School of Fear: The Final Exam. This study aims at describing the symptoms, the causes, and the effects of anxiety which is suffered by Mrs. Wellington. This study applies psychoanalysis theory by Sigmund Freud to analyze Mrs. Wellington’s anxiety. The symptoms of anxiety that is suffered by Mrs. Wellington are such as feeling anxious, being unable to think about anything but something that makes her anxious, and experiencing trembling, melancholy, and the deepest sadness. There are some causes of Mrs. Wellington’s anxiety. First, Mrs. Wellington’s anxiety is caused by her stepson, Abernathy, who hates her since he suffers from novercaphobia or well-known as fear of stepmother. The second cause is Sylvie Montgomery, the nosy reporter who always uses her nose to get information or disgraceful secret of Mrs. Wellington and all her students to make an article in order to win the Snoopulitzer, a contest for reporter in Summerstone. The effects of Mrs. Wellington’s anxiety are very complete. She feels the behavioral effect, the emotional effect, and the cognitive effect of her anxiety. It can be seen from her negative feeling because something in her past, she experiences trouble of concentrating, and she feels afraid every time she thinks about her fears. Mrs. Wellington’s anxiety is categorized of neurotic anxiety. Neurotic anxiety comes from id which is in the form of unconscious feeling so she often loses her emotion such as being sad, angry, panic, and so on. From the analysis, it can be concluded that Mrs. Wellington suffers from anxiety because her uncontrollable emotion: being anxious and being worried. Her stepson and Sylvie, the reporter, become the causes of her anxiety. She also feels the behavioral, emotional, and cognitive effects. Mrs. Wellington suffers from a type of neurotic anxiety as reflected in its symptoms, causes, and effects.
Neuromorphic computing device using optical shock waves

We experimentally demonstrate an optical machine learning scheme that uses spatial dispersive shock waves for performing classification and regression tasks. The nonlinear optical device is easy-to-train and reaches accuracies comparable to digital reservoir machines.
MaLTeSQuE 2021 Workshop Summary

The 5th edition of the Machine Learning Techniques for Software Quality Evaluation (MaLTeSQuE 2021) workshop was held virtually (originally in Athens, Greece) on August 23rd, 2021, colocated with the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2021). MaLTeSQuE received a total of ten submissions from all over the world, from which six papers and three abstracts were included in the program. The program also featured a keynote by Tim Menzies on the future of machine learning techniques for software quality. This report summarizes the event and insights stemmed from the keynote and presentations in the three sessions of the workshop.
Introducing Android

Welcome to the start of your developer journey with Android. Perhaps you already own and use an Android phone, tablet, or other devices. You would be in great company, with over a billion devices around the world used every day based on the Android operating system. Even if you think you don't already use Android, you may be surprised to learn that it has made its way into an astonishing range of devices and products, many of which you might have used without even realizing the power of Android was helping you out.
PENGARUH KOMUNIKASI INTERPERSONAL ORANG TUA DAN ANAK TERHADAP PRESTASI BELAJAR SISWA KELAS X

Interpersonal communication is one of communication methods that often used for communicates with others, no doubt. The success of parents and teachers in communicating are the important one. Because they are humans that we should imitated. According to explanation above, the writer can take three conclusions from this research are:Based on this research to know available or not the influencw of interpersonal communication of parents to the achievement of students of class I MA Nurul Huda Pangilen Dasuk Sumenep Year 2017/2018, it can be shown by T­hitung X1 2.589 &gt; Ttabel 2.026. Hence thus the working hypothesis (H1) which states that "there is influence interpersonal communication parent to learning achievement Class I MA Nurul Huda Pangeling Dasuk Sumenep 2017/2018" otherwise accepted. Based on the above research to find out whether or not the influence of interpersonal communication of children to the achievement of students of class I MA Nurul Huda Pangilen Dasuk Sumenep Year 2017/2018, it can be shown T­hitung X2 sebesar 1.361 &lt; Ttabel 2.026. Thus it is proven working hypothesis (H1) which states that "there is influence of parents' internal communication on learning achievement Class. According to the research above, knowing there is or not the effect of interpersonal communication between parents and children's achievement for student grade 1 MA (Islamic Senior High School) Nurul Huda pangilen Dasuk Sumenep 2017/2018. So, it can be counted as (F­hitung 4.834 &gt; Ftabel 3.25). So that way, it's been approved that work hypothesis (H1) which said that 'the effect of interpersonal communication between parents and children's achievement for student grade 1 MA Nurul Huda Pangeling Dasuk Sumenep 2017/2018 is accepted'From this research, it's concluded that the effect of interpersonal communication between parents and children's achievement for student grade 1 MA Nurul Huda Pangilang Dasuk Sumenep 2017/2018 accounted into medium category.
Improved Minimum Spanning Tree based Image Segmentation with Guided Matting

In image segmentation, for the condition that objects (targets) and background in an image are intertwined or their common boundaries are vague as well as their textures are similar, and the targets in images are greatly variable, the deep learning might be difficult to use.Hence, a new method based on graph theory and guided feathering is proposed.First, it uses a guided feathering algorithm to initially separate the objects from background roughly, then, the image is separated into two different images: foreground image and background image, subsequently, the two images are segmented accurately by using the improved graph-based algorithm respectively, and finally, the two segmented images are merged together as the final segmentation result.For the graph-based new algorithm, it is improved based on MST in three main aspects: (1) the differences between the functions of intra-regional and inter-regional; (2) the function of edge weight; and (3) re-merge mechanism after segmentation in graph mapping.Compared to the traditional algorithms such as region merging, ordinary MST and thresholding, the studied algorithm has the better segmentation accuracy and effect, therefore it has the significant superiority.