Reviewerly/exHarmony huggingface dataset:
Continual Learning of Generative Models with Limited Data: From Wasserstein-1 Barycenter to Adaptive Coalescence

Learning generative models is challenging for a network edge node with limited data and computing power. Since tasks in similar environments share model similarity, it is plausible to leverage pre-trained generative models from the cloud or other edge nodes. Appealing to optimal transport theory tailored towards Wasserstein-1 generative adversarial networks (WGAN), this study aims to develop a framework which systematically optimizes continual learning of generative models using local data at the edge node while exploiting adaptive coalescence of pre-trained generative models. Specifically, by treating the knowledge transfer from other nodes as Wasserstein balls centered around their pre-trained models, continual learning of generative models is cast as a constrained optimization problem, which is further reduced to a Wasserstein-1 barycenter problem. A two-stage approach is devised accordingly: 1) The barycenters among the pre-trained models are computed offline, where displacement interpolation is used as the theoretic foundation for finding adaptive barycenters via a "recursive" WGAN configuration; 2) the barycenter computed offline is used as meta-model initialization for continual learning and then fast adaptation is carried out to find the generative model using the local samples at the target edge node. Finally, a weight ternarization method, based on joint optimization of weights and threshold for quantization, is developed to compress the generative model further.
Cyclic and constacyclic codes over the ring Z4[u]/⟨u3 − u2⟩ and their Gray images

In this article, the structure of generator polynomial of the cyclic codes with odd length is formed over the ring Z4 + uZ4 + u 2 Z4 where u 3 = u 2 .With the isomorphism we have defined, the generator polynomial of constacyclic codes with odd length over this ring is created from the generator of the cyclic codes.Additionally, necessary and sufficient conditions for a linear code in this ring to be a self dual code and a LCD code are mentioned.Furthermore, for all units over this ring, Z4 -images of λ -constacyclic codes and also Z4 -images of cyclic codes are examined by using related ones from defined three new Gray maps.Moreover, several new and optimal codes are constructed in terms of the Lee, Euclidean and Hamming weight in reference to the database.
Bitcoin as an Alternative Digital Currency. Exploring the Public’s Perception vs Experts.

This paper attempts to find out if the view of the public coincides with the opinion of the experts on the Bitcoin’s subject and to determine if is information can be implemented in order to establish a use of Bitcoin in our everyday lives. During the first stage of this research, methods and rules of analysis such as descriptive statistics and tables and charts were used. Firstly, a questionnaire was used and secondly, the answers were gathered and classified according to the participants’ choices. During the second stage, the data was collected with the use of random sampling, while various techniques, such as simple and multiple regressions were utilised for analysing the results. The conclusion is that the public perceives Bitcoin differently than the experts do. Individuals believe that Bitcoin is mainly a means of transactions/payments, contrary to the experts’ opinion, which is that it is foremost an investment asset.
Em época de Pandemia: Covid-19 como Doença Profissional- a experiência de um Instituto Português de Oncologia

INTRODUCTION The novel coronavirus, called SARS-CoV-2, has as its main factor of the disease spreading the transmission between humans. COVID-19 is the name given by the World Health Organization (WHO) to identify the disease caused by this agent. Portugal is currently experiencing the pandemic Mitigation phase, in which, in addition to community transmission, it is assumed that there is local transmission in a closed environment. This disease was recognized by the WHO and by the Portugal Directorate-General of Health as Occupational Disease in a health care environment. OBJECTIVE Evaluate and characterize the presumed cases of occupational disease caused by SARS-CoV-2, among workers with COVID-19, considering the respective interpretation of the causal nexus, individually. METHODS Retrospective, descriptive, observational study (case-series), carried out between march and july 2020 in workers of a Portuguese oncology institute, dedicated to provide care for patients with cancer, reviewing files in the clinical processes of the occupational health service software (UTILSST®). It was considered the infection of workers with SARS-COV-2, as an inclusion criterion. RESULTS 41 workers were diagnosed with COVID-19, with an average age of 43.70 ± 11.63 years. Of these, 87.80% (n= 36) were female. The professional category with the highest infection rate in the institution was the auxiliaries of nursing [46.34%, n= 19], followed by nurses [39.02%, n = 16]. The most affected service was a Medical Oncology Service [31.4%, n= 11]. In the studied population, the prevalence of cases presumed to be Occupational Disease was 80.49% (n= 33). Of these, 48.5% (n= 16) were by direct contact with an infected patient, 30.3% (n = 10) without a known index case, but with a diagnosis obtained in “Disease mitigation phase” and 21.2% (n=7) by contact with an infected worker. In 19.51% (n= 8) of all the cases, no Occupational Disease was presumed, due to contact with an infected index case in a social/ family environment. CONCLUSION The main sources of nosocomial transmission with an assumed causal nexus are patients with COVID-19. It is essential to put into practice and ensure the maintenance of adequate collective and individual protection measures to combat this disease, as well as ensuring a permanent update of the institution’s infection control program so that the risk of exposure is controlled.
Indexes and Foreign Keys

In the previous chapter, you learned how indexes and foreign keys can influence locking. This is a topic that is worth diving further into as it is important to understand the effects.
Strategi Pengembangan Content Based Video Retrieval Di Perpustakaan Sekolah Tinggi Multi Media MMTC Yogyakarta

ABSTRACT&#x0D; &#x0D; Introduction One of the efforts to provide the best service for users is by developing innovative library services. One of them is by developing a video content-based library collection. MMTC Yogyakarta Multi Media College Library has developed a video content-based information retrieval system. It is hoped that by utilizing this video content-based STKI, users will be helped and get accelerated information in finding the material needed, especially searching for material in video files.&#x0D; Data Collection Method. In this paper the writer uses qualitative research with a library research approach, while the data analysis uses content analysis techniques. This method the authors use to observe and analyze an information system.&#x0D; Results and Discussions. In developing a Content Based Video Retrieval strategy in the MMTC Yogyakarta Multi Media High School Library, it begins with identifying user needs, creating a system design, evaluating the system design, pouring the system design into a programming language, testing the system, evaluating the system and using it. Then, the authors also provide an overview of the development of the STKI by conducting a SWOT analysis. Based on the macro analysis, the opportunity and threat variables will be formulated, while the internal analysis will formulate the strength and weakness variables. The last stage is the STKI analysis, while the stages are: complete definition, problem analysis, needs analysis, logic design and needs analysis.&#x0D; Conclusions. In the Content Based Video Retrieval development strategy at the MMTC Yogyakarta Multi Media College Library, there are several things that need to be considered in the development of an information retrieval system, including: User needs, development budget (budget), human resources, support from leaders and facilities (software and hardware) and IT infrastructure (internet network). The development of the STKI should begin with identifying user needs and conducting a SWOT analysis to determine the strengths and weaknesses of the system, as well as the goal so that the system can be optimally empowered by users.&#x0D; &#x0D; Keywords: Library, Information Retrieval System, Video Content
Forecasting of New Ore Areas Based on Geophysical Data

Summary The possibility of regional forecasting of new ore regions using freely available gravimetric and magnetic data is discussed. Summary matrices of gravitational and magnetic anomalies with a cell size of 2 * 2 km are used. Is Shown that with this grid, using of analytical methods is not effective, and probabilistic and statistical analysis technologies will be more effectively. The possibilities of effective solution of the problem based on the analysis of anomalous fields and their transformations using statistical methods, including lineament and cluster analysis, as well as formal prediction of mineralization using image recognition algorithms with training on reference objects are shown. As standards, both deposits and ore occurrences within the work contour and external significant objects are used.
Self-labeling of Fully Mediating Representations by Graph Alignment

To be able to predict a molecular graph structure (W) given a 2D image of a chemical compound (U) is a challenging problem in machine learning. We are interested to learn $$f: U \rightarrow W$$ where we have a fully mediating representation V such that f factors into $$U \rightarrow V \rightarrow W$$ . However, observing V requires detailed and expensive labels. We propose graph aligning approach that generates rich or detailed labels given normal labels W. In this paper we investigate the scenario of domain adaptation from the source domain where we have access to the expensive labels V to the target domain where only normal labels W are available. Focusing on the problem of predicting chemical compound graphs from 2D images the fully mediating layer is represented using the planar embedding of the chemical graph structure we are predicting. The empirical results show that, using only 4000 data points, we obtain up to 4x improvement of performance after domain adaptation to target domain compared to pretrained model only on the source domain. After domain adaptation, the model is even able to detect atom types that were never observed in the original source domain. Finally, on the Maybridge data set the proposed self-labeling approach reached higher performance than the current state of the art.
E-Lelang Barang Antik Berbasis Mobile Pada Komunitas Pecinta Antik Kreatif Sriwijaya Palembang Menggunakan Metode Mobile-D

At this time antiques are increasingly in demand by many people.in Kompaks (Sriwijaya creative antique lovers community) Palembang introduces the history of these antiques such as furniture, weapons, art items, household items and other art items.besides that, compact also conducts antique auction.Antiques auction is done at the compact post itself and also at events related to history and antiques.from the auction process the time needed for the auction to be compact is longer and bidders must visit the tender process location and follow all the process activities that take place. With these problems, the researcher will make an e-auction (electronic auction) antiques application that will work according to the established auction rules. This e-auction application uses the mobile-D method which is one method that is suitable for the development of mobile applications because it is agile and flexible. so with this application it is expected to make it easier to conduct auction activities that are not limited by time and place.
Video Summarization: Study of various techniques

A comparative study of various techniques which can be used for summarization of Videos i.e. Video to Video conversion is presented along with respective architecture, results, strengths and shortcomings. In all approaches, a lengthy video is converted into a shorter video which aims to capture all important events that are present in the original video. The definition of 'important event' may vary according to the context, such as a sports video and a documentary may have different events which are classified as important.
FLASHCARD AS A MEDIA TO IMPROVE STUDENTS’ WRITING SKILL IN DESCRIPTIVE PARAGRAPH

The main purpose of this research is to know the improvement of students’ writing skill in descriptive paragraph through flashcard media. This research was conducted at SMP “Empat Lima” Karanggeneng. This research is a classroom action research which consisted of two cycles. This study was carried out on February until May 2020. The subjects were the seventh grade students of SMP “Empat Lima” Karanggeneng, Lamongan. The data were collected by holding the test, interviewing, observing and distributing the questionnaire. The instruments that have been used are writing paragraph rubric, interview guideline, observational note and questionnaire sheet. The data that were used in this research are qualitative dan quantitative. This study used democratic validity, outcome validity, catalytical validity, process validity and dialogic validity as the validation. Then, the reliability of this study were time and investigator triangulation. There were several steps in this research implememntation, they are identifying the problems, planning, acting, observing and reflecting. The results showed that the use flashcard media in writing has been able to improve students’ writing skill. According to the qualitative data, the students were enjoy and enthusiastic with the implementation of flahcard media in writing lesson. The They also felt easier to make a descriptive paragraph through this media. According to the quantitative data, the students’ main score was improved in the each cycle. Keywords: : Flashcard, writing skill
Review of Open and equitable scholarly communications: Creating a more inclusive future

Abstract: Review of Maron, N., Kennison, R., Bracke, P., Hall, N., Gilman, I., Malenfant, K., Roh, C., & Shorish, Y. (2019).  Open and equitable scholarly communications: Creating a more inclusive future.  Chicago: Association of College and Research Libraries.
Knowledge Graph Embeddings for Dealing with Concept Drift in Machine Learning

Stream learning has been largely studied for extracting knowledge structures from continuous and rapid data records. However, efforts to understand whether knowledge representation and reasoning are useful for addressing concept drift 1 , one of the core challenges from the stream learning community, particularly those due to dramatic changes in knowledge, have been limited and scattered. In this work, we propose to study the problem in the context of the semantic representation of data streams in the Semantic Web, i.e., ontology streams. Such streams are ordered sequences of data annotated with an ontological schema. A fundamental challenge is to understand what knowledge should be encoded and how it can be integrated with stream learning methods. To address this, we show that at least three levels of knowledge encoded in ontology streams are needed to deal with concept drifts: (i) existence of novel knowledge gained from stream dynamics, (ii) significance of knowledge change and evolution, and (iii) (in)consistency of knowledge evolution. We propose an approach to encoding such knowledge via schema-enabled knowledge graph embeddings through a combination of novel representations: entailment vectors, entailment weights, and a consistency vector. We illustrate our approach on supervised classification tasks. Our main findings are that: (i) It is possible to develop a general purpose framework to address concept drifts in ontology streams by coupling any machine learning classification algorithms with our proposed schema-enabled knowledge graph embeddings method; (ii) Our proposed method is robust to significant concept drift (up to 51% of stream update ratio) and out-performs state of the art methods with 12% to 35% improvement on the Macro-F1 score in the tested scenarios; (iii) Only a small part of the ontological entailment (less than 20%) play an important role in determining the consistency between two snapshots; (iv) Predictions with consistent models outperform those with inconsistent models by over 300% in the two use cases. Our findings could help future work on applications of stream learning, such as autonomous driving, which demand high accuracy of stream learning in the presence of sudden and disruptive changes.
Formation of clinical thinking with the use of human-like robots

Due to the fact that students rarely take part in diagnostic and therapeutic activities, there is a huge gap in the practical medical practice. To replenish it, there is the possibility of introducing humanoid robots with various scenarios into the educational process for the correct formation of professional skills and clinical thinking of students and young doctors.
EFFECT OF INFORMATION AND COMMUNICATION TECHNOLOGY ON THE ATTAINMENT OF MILLENNIUM DEVELOPMENT GOALS (MDGS) IN NIGERIA, (A CASE STUDY OF PAMPAIDA MILLENNIUM VILLAGE, KADUNA STATE, NIGERIA.

The study examines the effects of information and communication technology (ICT) on the attainment of the Millennium Development Goals (MDGs) in Nigeria from 2006 to 20015 with specific focus on effects of mobile phone, Internet, Computer and Radio on MDGs. Four research questions and four hypotheses were tested at 5% level of significance. The design for this study was a survey design while the population was made up of Five Thousand Six Hundred and Sixty-Six (5,666) people living in Pampaida Millennium Village. The sample size was Three Hundred and Seventy-Four (374). The sampling technique used is convenient sampling. The method of data collection used was questionnaire for primary data. Method of data analysis were percentages, linear regression and analysis of variance. The data analysis revealed that the ICT factors that have meaningful impact on MDGs were Mobile phones, Internet and Radio. Mobile phones were the widely use ICTs within the study area followed by Radio and Internet respectively. Computer usage within the village was quite low; this calls for integration of computer education in adult and non-formal system of education, which is the major source of education within the community
DESIGN AND FABRICATION OF AUTOMATIC SPROUTING MACHINE

Through newspapers, television and the Internet information, self-cultivation of sprouting in the household as well as the trading model are very popular in the country. Particularly, when a plantbased stimulants information is widespread, self-cultivation of household sprouting becomes increasingly urgent. Current seed nursery machine in the market are not attractive to the user, which is mainly due to lack of user convenience. Thus, the fully automatic machine with a good price will create a special appeal to everyone. For this reason, this paper designs and fabricates sprouting machine automatically. Users do not need to operate the device during the sprouting development, but still ensure 100% success rate of high quality produce. In addition, the device can optimize important parameters affecting of sprouting development such as humidity, temperature, air and water. Sprouting are always in the best growth state, shorten the time to harvest products as a result.
Automatic Detection and Classification of Unconformities on Seismic Data Using Machine Learning

Summary During a seismic interpretation exercise, picking an unconformity is one of the most time-consuming and ambiguous tasks. In this paper we present a method to quickly detect areas that are highly likely to be an unconformity, using the principle that at angular unconformities the azimuth and dip of the strata changes. We introduce a workflow to classify what kind of unconformity has been detected, by feeding the areas with high unconformity probabilities into a convolutional neural network. This adds the benefit that one can quickly discern whether the region was associated with significant uplift or not.
Phonemic Variations in Similar Words of Urdu and Turkish Languages

Urdu language is a member of Indo-European family tree and within the zone of Indo-Iranian branch, whereas Turkish language is a member of Altaic family tree. Both of these languages belong to different family trees, but these languages have many words in common. Urdu language has 41 consonant sounds and 11 vowel sounds, whereas Turkish language has 21 consonant sounds and 8 vowel sounds. Both of these languages donâ€™t have same number of phonemes. It is interesting to contemplate, how the speakers of both languages produce and perceive these common words in their languages. Therefore, a study is designed to explore the phonemic variations in similar words of Urdu and Turkish languages. In order to find out variations, a list of 75 words, which are common in Urdu and Turkish language was prepared in form of text. The data of this study was collected from Pak-Turk school of Lahore. The prepared words list was given to 10 Turkish speakers. These speakers were selected by using purposive sampling technique. The audios of the speakers were recorded and transcribed into standard Turkish IPA symbols. Levenshtein algorithm framework is used to draw a comparative analysis of Turkish phonemic transcriptions with standard Urdu phonemic transcriptions of the same words. With the help of Levenshtein algorithm, phonemic variations in similar words of both languages was measured. The intriguing result of the study will help in establishing the understanding about the production directions of the similar words used by the speakers of both languages.
AHMoSe: A Knowledge-Based Visual Support System for Selecting Regression Machine Learning Models

Decision support systems have become increasingly popular in the domain of agriculture. With the development of Automated Machine Learning, agricultural experts are now able to train, evaluate and make predictions using cutting edge machine learning (ML) models without the need for much ML knowledge. Although this automated approach has led to successful results in many scenarios, in certain cases (e.g., when few labeled datasets are available) choosing among different models with similar performance metrics is a difficult task. Furthermore, these systems do not commonly allow users to incorporate their domain knowledge that could facilitate the task of model selection, and to gain insight into the prediction system for eventual decision making. To address these issues, in this paper we present AHMoSe, a visual support system that allows domain experts to better understand, diagnose and compare different regression models, primarily by enriching model-agnostic explanations with domain knowledge. To validate AHMoSE, we describe a use case scenario in the viticulture domain, grape quality prediction, where the system enables users to diagnose and select prediction models that perform better. We also discuss feedback concerning the design of the tool from both ML and viticulture experts.