Reviewerly/exHarmony huggingface dataset:
Understanding the Broader Aspect of Blockchain Technology As Well as Cryptocurrency and Its Limitless Application for the Economy &amp;amp; Society

20 Years ago, the world start changing in a very different way. The Internet was a wild west. Lots of pioneers of the different field set out to explore this field and find the opportunity. Many failed in these expeditions but some survived and tiny few succeeded and transform the world forever. Today block-chain is that new wild west. The revolutionary technology will transform every single business in the next 10 years. Block-chain is one of the biggest disruptive technology of the coming decades. In this paper, I am trying to find the possible use cases of block-chain technology. This technology has a much wider application and not limited to cryptocurrency. Here we set out to explore the possible areas where we can apply block-chain technology to make it more robust, more reliable, and more secure. We will also try to find investment methods in cryptocurrencies. Let’s transform the world together.
Knowledge Graph Personalization by Estimation of Interest in Various Concepts

In this paper, we propose a new personalization method for knowledge graphs using a graph convolutional neural network. As personalized items user interests are treated. Hobbies are used as an example of interest in this paper. Personalized data is obtained from labeled concepts rather than text. In the proposed method, the knowledge graph constructed from the Japanese WordNet and ALAGIN word co-occurrence dictionaries and GCN (Graph Convolutional Networks) are employed. Whether or a user is interested in each concept in the knowledge graph is estimated by three elements: interest data; graph structure of the hobby as an example; and GCN. As a result of the evaluation experiment, the proposed method obtained good results on predicting unknown subjects of interests.
Design And Implementation Of Customized Programs In Continuing Professional Education

The urgency of implementing a customized approach in continuing professional education as a strategy for its modernization to solve the problems of economic and social sustainable development of modern society has been explained. The method of comparative analysis has been used to study various approaches to understanding the term "customization". It is shown that concerning continuing professional education, customization means the compliance of goals, objectives, content and expected results to the current needs of a customer of a continuing professional program, the distinctive feature of which is using a “package” of programs with different “depths” of customization united in one topic. It has been proved that the customized approach fundamentally changes the nature of the interaction between the organization of continuing professional education and a customer of educational services. It has been stated that the use of customized approach in continuing professional education has practically not been studied. The author's algorithm for designing customized continuing professional programs, including four stages, is the following: collaborative customization through dialogical interaction with the customer; determination of the type and depth of customization; content filling, choice of methods and technologies, development of methodological support; approbation; students’ reflection and analysis of the training effectiveness.
Formation of Professional Qualities in Students

Since gaining independence, our country has begun to carry out radical reforms in various sectors of the economy in order to become one of the most developed countries in the world. In particular, in the field of education, as a result of the adoption of the law On Education and the legislation, a scientific system of training qualified personnel in the system of continuing education has been developed.
Critical Thinking in Media Sphere: Attitude of University Teachers to Fake News and Its Impact on the Teaching

The article aims to determine how university professors critically perceive and evaluate information when interacting with the media sphere. The study's relevance is due to the insufficient elaboration of Russian teachers' attitude to the information in the media sphere. which is significant in developing students' critical thinking. The study analyzes theoretical sources and documents on critical thinking in the media sphere and the results of processing empirical data obtained from questioning teachers. The main measuring instrument is a questionnaire survey of university professors with various lengths of service. The study involved 76 teachers from Ural Federal University named after the first President of Russia B.N. Yeltsin. Ural State Pedagogical University (Ekaterinburg, Russia). Linguistics University of Nizhny Novgorod (Nizhny Novgorod, Russia). The data obtained from the study of the teachers' attitude to the information content of the media sphere show a predominant critical attitude in assessing the reliability and availability of information on social networking platforms. This conclusion is important for personality traits that develop students' critical thinking.
Rethinking What We Owe Each Other

Note: This commentary was first published on 13 August 20201 by Singapore Policy Journal at the Harvard Kennedy School. A link to the original publication can be found here: https://spj.hkspublications.org/2021/08/13/rethinking-what-we-owe-each-other/This commentary explores our moral obligations to one another during COVID-19. It discusses the importance of social responsibility and how it maps onto the provisions and shortcomings of existing tracking technologies used to curb the spread of the virus. From the angle of beneficence – acting to promote good to others and the common good – we explore possibilities for our control strategies and the community going forward.
LSB Technique-Based Dual-Image Steganography Using COS Function

Due to the advancement in technology, the exchange of information via a network has been taking such a great peak that each and every person is highly dependent on the Internet, like in the current Covid-19 pandemic situation. But sharing information/secret medical data by means of the Internet has created a risk to the information loss. Thus, data exchange should be done in such a way that its presence cannot be perceived by the third party with bad intentions and should not be able to modify or alter the important message. For the safety of important data, many algorithms like cryptography, steganography, watermarking, etc. have been used by researchers to safeguard data sharing via an insecure Internet. Cryptography and steganography together can provide better security to the data as one encrypts the data and the other hides its presence in multimedia, like image, audio, video, etc. In this paper, data encryption and image steganography have been presented to provide security to the message that is being transferred through the Internet. The experimental outcomes show that the proposed technique is able to transfer important data securely without coming into the eyes of a hacker. The PSNR value for the proposed system is about 51.14 with 1 bit per pixel (bpp) capacity. As per the security view, the presented method has a 7.99 entropy value, which means the system is secure against attacks.
Unsupervised 3D Pose Estimation for Hierarchical Dance Video Recognition

Dance experts often view dance as a hierarchy of information, spanning low-level (raw images, image sequences), mid-levels (human poses and bodypart movements), and high-level (dance genre). We propose a Hierarchical Dance Video Recognition framework (HDVR). HDVR estimates 2D pose sequences, tracks dancers, and then simultaneously estimates corresponding 3D poses and 3D-to-2D imaging parameters, without requiring ground truth for 3D poses. Unlike most methods that work on a single person, our tracking works on multiple dancers, under occlusions. From the estimated 3D pose sequence, HDVR extracts body part movements, and therefrom dance genre. The resulting hierarchical dance representation is explainable to experts. To overcome noise and interframe correspondence ambiguities, we enforce spatial and temporal motion smoothness and photometric continuity over time. We use an LSTM network to extract 3D movement subsequences from which we recognize the dance genre. For experiments, we have identified 154 movement types, of 16 body parts, and assembled a new University of Illinois Dance (UID) Dataset, containing 1143 video clips of 9 genres covering 30 hours, annotated with movement and genre labels. Our experimental results demonstrate that our algorithms outperform the state-of-the-art 3D pose estimation methods, which also enhances our dance recognition performance.
DEVELOPING ENGLISH LANGUAGE ACQUISITION WITH SUPPLEMENTARY MATERIAL THROUGH MOBILE ASSISTED LANGUAGE LEARNING FOR INFORMATION ENGINEERING STUDENTS OF PAMULANG UNIVERSITY

High expectation on learning outcome must get along with the teaching process. English acquisition for informatics engeneering students will be problem wihout the support of  mobile Technology. Limited time is always be the reason why English learning outcome is not maximal. The aim of this research to find out  what strategy should apply to  to accomplish the learning outcome. And to find out how effective to use mobile learning to help Informatic Engeneering students  to get the target of the learning outcome. This study, therefore, aims at improving Englih acquisition by giving them supplementary material  through Mobile–learning. This study was a classroom action research, which was carried out in three cycles. The participants of the research were first semester of Informatic Engenering students in Pamulang University.  The finding, the improvement of grammar is 7%, the pre-test result was 68,5% and after the implementation of suplementary material through MALL, it creased to 75,5% while reading comprehension from 61,08 % increased to 74.9%. it is significant improvement.
Ensemble Case based Reasoning Imputation in Breast Cancer Classification.

Missing Data (MD) is a common drawback that affects breast cancer classification. Thus, handling missing data is primordial before building any breast cancer classifier. This paper presents the impact of using ensemble Case-Based Reasoning (CBR) imputation on breast cancer classification. Thereafter, we evaluated the influence of CBR using parameter tuning and ensemble CBR (E-CBR) with three missingness mechanisms (MCAR: missing completely at random, MAR: missing at random and NMAR: not missing at random) and nine percentages (10% to 90%) on the accuracy rates of five classifiers: Decision trees, Random forest, K-nearest neighbor, Support vector machine and Multi-layer perceptron over two Wisconsin breast cancer datasets. All experiments were implemented using Weka JAVA API code 3.8; SPSS v20 was used for statistical tests. The findings confirmed that E-CBR yields to better results compared to CBR for the five classifiers. The MD percentage affects negatively the classifier performance: as the MD percentage increases, the accuracy rates of the classifier decrease regardless the MD mechanism and technique. RF with E-CBR outperformed all the other combinations (MD technique, classifier) with 89.72% for MCAR, 87.08% for MAR and 86.84% for NMAR.
Rhino Mano Ventures : Genius Purse Tracker / Muhamad Alif Hanifa Mohd Asri [et al.]

The leather wallet industry is an expansive and resistant industry where the demands are increasing constantly due to the increase in population. This industry is one of the influential industries to the income of the nation. On top of that, with electronic industry, it can improve living standards foster the growth of the leather wallet and goods market. Global market players continuously launch latest and stylish leather goods according to the changing demand of consumers.The wallet is made from premium and high quality of leather which follow the changing of fashion trends. Apart from that, it also provides GPS tracker and Bluetooth buzzer to help the user that lost their wallet or purse. In Malaysia, this product is recent introduced to the people either children or teenagers nor adults and older .With the increase in population, the demand of this product will very much likely to be increased.The production of genius purse tracker has long shelf life and has the potential to be exported to other countries. This allows our company to sell the products overseas increasing the market size and sales of company
THE ENHANCING OF SPEAKING SKILL THROUGH THE APPLICATION OF COMMUNICATIVE LANGUAGE TEACHING (CLT) METHODE AT X RESTAURANT CLASS OF STATE VOCATIONAL HIGH SCHOOL PRAYA TENGAH

English is an International language that widely used in Indonesia begining from Play Group to the University. Learning English is a must for the students in all of the schools, especially in State Vocational High School Praya Tengah. Being one of the most important subjects that need to be comprehended and mastered by its user. The main problem of this research is the Speaking Skill of X Restaurant students have not maximized. Therefore, it would be needed to use a teaching learning methode to enhance their skill in Speaking English. Communicative Language Teaching (CLT) is one of the methodes used in teaching learning process. Using this methode, hopefully the students’ English achievement especially in Speaking Basic Competency 5th which is Describing Events will be enhanced.The main objective of this research is to improve the teaching learning English in Speaking skill especially Describing Events that can be easier to be comprehended by the students through Communicative Language Teaching (CLT) methode. The action Hypotheses made by the researcher is “Communicative Language Teaching (CLT) methode will enhance the Students’ Speaking Skill in Learning English”.This research used Classroom Action Research that has four stages: 1) Plan, 2) Action, 3) Observation, and 4) Reflection. These four stages are organized in two cycles. The sources of data are the  Speaking achievement  of    X Restaurant  students and photograph. The data of the research are the students’ achievement, and  the students’ process achievement, recorded of oral test, and observation.Based on the analysis result, it was found that the average of the students’process achievement in the first cycle is 63.71, and in the second cycle is 65.62. The average of the students’achievement in the first cycle is 87.50, and in the second cycle is 91.88. It is significantly change. Therefore, the English  teaching learning process through Communicative Language Teaching (CLT)  methode can enhance the students’Speaking ability. Communicative Language Teaching (CLT) methode makes the classroom situation become attractive, variative, and joyful.
To Detection and Recognition of Marathi Text from Handwritten Document Images using Deep Learning

: Handwritten character identification from a realistic picture presents many challenges. Bangla characters are made up of a lot of different forms and strokes. Deep learning has recently developed practical skills for extracting high-level features from an image kernel. This article will show how to combine a multilayer convolutional neural network, an origination module, and a fully connected network in a new way. In this system, we proposed a hybrid CNN based handwritten character recognition using deep learning techniques. Various feature extraction and selection techniques have been used during the module training and testing, respectively. In an extensive experimental analysis, we have tested around 5800 image datasets with various cross-validations. The accuracy of proposed system is around 95.20% and evaluated with numerous state-of-arts system.
외국인 유학생 대상 e-PBL 대학 글쓰기 수업 사례 연구

The purpose of this study is to present examples of e-PBL application in liberal arts writing courses for foreign undergraduates. We presented how writing classes at universities applying e-PBL were conducted for foreign students attending K University. Based on the results of the learners calculated at each stage of e-PBL, it was revealed that e-PBL lessons were feasible for foreign students. Furthermore, we were able to derive their characteristics. According to a survey of students’ satisfaction, foreign students were satisfied with e-PBL. However, e-PBL confirmed that there are space-time constraints and that it is difficult to solve the problem of reducing the satisfaction of learners such as free riders. This paper presents the direction of the course that aim to solve these problems. (Korea University)
Sharks, Zombies and Volleyball: Lessons from the Evolutionary Computation Bestiary

The field of optimization metaheuristics has a long history of finding inspiration in natural systems. Starting from classic methods such as Genetic Algorithms and Ant Colony Optimization, more recent methods claim to be inspired by natural (and sometimes even supernatural) systems and phenomena - from birds and barnacles to reincarnation and zombies. Since 2014 we publish a humorous website, The Bestiary of Evolutionary Computation, to catalog these methods, witnessing an explosion of metaphor-heavy algorithms in the literature. While metaphors can be powerful inspiration tools, we argue that the emergence of hundreds of barely discernible algorithmic variants under different labels and nomenclatures has been counterproductive to the scientific progress of the field, as it neither improves our ability to understand and simulate biological systems, nor contributes generalizable knowledge or design principles for global optimization approaches. In this short paper we discuss some of the possible causes of this trend, its negative consequences to the field, as well as some efforts aimed at moving the area of metaheuristics towards a better balance between inspiration and scientific soundness.
Digital assets and property rights in insolvency

Abstract What happens to your Bitcoin or other cryptoassets if the custodian becomes insolvent? In the rush to investment in these alternative currencies, little attention has been paid to this consequence, not least by the custodians and exchanges themselves, as amply demonstrated by the case considered in this article. At the same time, we consider the solution to the problems presented in a number of insolvency cases around the world, by the comprehensive cryptoasset legislation introduced by the State of Wyoming, USA.
Membership Inference Attacks Are Easier on Difficult Problems

Membership inference attacks (MIA) try to detect if data samples were used to train a neural network model, e.g. to detect copyright abuses. We show that models with higher dimensional input and output are more vulnerable to MIA, and address in more detail models for image translation and semantic segmentation, including medical image segmentation. We show that reconstruction-errors can lead to very effective MIA attacks as they are indicative of memorization. Unfortunately, reconstruction error alone is less effective at discriminating between non-predictable images used in training and easy to predict images that were never seen before. To overcome this, we propose using a novel predictability error that can be computed for each sample, and its computation does not require a training set. Our membership error, obtained by subtracting the predictability error from the reconstruction error, is shown to achieve high MIA accuracy on an extensive number of benchmarks.
An Extracting and Labeling Algorithm for Connected Components in Images

Image connected region labeling can effectively improve the efficiency of subsequent image analysis and processing tasks. Many achievements have been made, but there is no labeling algorithm for color images. Therefore, we propose a multi-class dynamic labeling(MCDL) algorithm. We construct the mathematical model of the MCDL algorithm first. And then, a series of new concepts, such as run, affecting scope and column coordinate set, are put forward. Based on these concepts, the judgment criterion on connection of two runs is defined with set operations. Next, a theorem is given and proofed to limit the number of provisional labels, and a class example is used to demonstrate operations of the MCDL algorithm. After that, the storage model of results is described. Finally, the implement of the MCDL algorithm is discussed. The MCDL algorithm is distinct from all conventional algorithms mainly on two aspects: it can label both binary images and color images, and these images may be irregular, but the conventional algorithms label only N×N or N×M binary images; it not only labels but also extracts the connected components in an image, whereas the conventional algorithms just label them. Comparisons and experimental results on various types of images show that the MCDL algorithm is efficient and robust.
KUALITAS LAYANAN DONGENG ANAK DAN REMAJA KELILING (DARLING) DI DINAS PERPUSTAKAAN DAN KEARSIPAN PROVINSI JAWA TIMUR

In carrying out its functions, the library is one of the government institutions that are required to provide public services. Service is the most important element in the process of library activities. Therefore the library is required to provide a quality service to fulfill community needs because good library services will be able to attract the community. Through the Children and Teenagers Fairy Tale service (DARLING) is a tangible proof of public service innovation that can meet people's needs through children's stories. The existence of these services is expected to be able to generate interest in reading children from an early age. It is necessary to improve the quality of public services because it is a real attitude of the government in carrying out the performance, responsibilities, and commitment of service provider organizations in relation to the needs, demands and interests of the community. The government makes efforts to improve the quality of public services with various strategies in the hope of future changes. This research is a qualitative descriptive study with data collection techniques in the form of observation, interviews, and documentation. Meanwhile, the focus of this research can be seen from the dimensions of Tangible, Reliable, Responsiveness, Assurance, and Empathy. The results of the study show that the quality of the Aroundland Children and Youth Tale (DARLING) service in the Library and Archives Service of East Java Province has been well implemented, so that in the process of service community satisfaction can be achieved.Keywords: Public Services, Service Quality
COVID-19, GUERRA SEM TRÉGUA

The COVID-19 pandemic has brought immeasurable impacts, disruption and losses. This terrible disease has been spreading devastatingly across the planet. A lethal and deadly virus, which unleashed a relentless war. COVID-19 results from the multidimensional crisis of civilization, mainly due to environmental destruction, ecosystemic imbalances and incapacity for health governance in the global and national context. The alternatives for reforms and transformations of the system go through policies of sustainable development and multilateral cooperation.