Reviewerly/exHarmony huggingface dataset:
A Wearable Patient Healthcare Monitoring System Using IoT and Cloud Computing Based Security

Now-a-days, a developing number of individuals at some point of a developing international locations like India forces to seem for brand spanking new answers for the persistent tracking of fitness check-up for stable data. It’s emerge as a need to go to hospitals frequently for doctor’s consultation, which has Growth to be financially associated and a time ingesting process. To beat this situation, we endorse a design to observe the patient’s fitness situations like heartbeat, temperature, ECG and BP and ship the message to guardian the use of GSM. Within the recent improvement of internet of factors (IoT) makes all objects interconnected and cloud been diagnosed due to the fact the subsequent technical revolution and now not secure for patient data. Patient monitoring is one a few of the IoT application to watch the affected person fitness status to collect facts to security for both medical doctor and patients Internet of things makes clinical equipment greater efficient with the aid of allowing actual time tracking of health in security privateness of the patient. Using IoT doctor can continuously monitor the patient’s cloud the usage of protection on his smartphone and also the affected person history could be stored on the web server and health practitioner can get entry to the statistics on every occasion wished from anywhere.
Aplikasi Laporan Transaksi Keuangan Pada Showroom Yas Motor Barabai Berbasis Android

The rise of developments in the world of technology today in the field of computers and telecommunications. Giving a significant impact of change, along with that the progress of the development of internet technology and mobile devices and also the existing operating system. The use of mobile devices as well as the open nature of the Android operating system allows the developer to modify freely and in accordance with the wishes of the client as to what applications will be made. YAS MOTOR BARABAI is a business unit or showroom engaged in the business of buying and selling used motorcycles. In line with current technological developments, YAS MOTOR BARABAI should utilize the technology to advance the work ethic of business units so that they can compete and survive in their business ventures. YAS MOTOR BARABAI during handling this business each transaction still applies the manual method of large bookkeeping, so that the report takes a long time. From these problems, an information system based on android application based on android application was formed which contained data on motorcycle sales and purchases that took place every day. The result of this research is an Android-based financial transaction report application design in the form of convenience to the owner of YAS MOTOR BARABAI in the process of working out financial transaction report data in a detailed and structured manner.
Informational Technologies As A Factor Of Self-Education For A Future Music Teacher

The urgency of the studied problem is justified because of the fact that in conditions of permanent scientific, technical, social and cultural changes in the society f a music teacher's personality with the multivalent qualification has gained significance, so that the teacher can both lead high standard professional activity using modern technologies and work on improvement of their qualification during the whole lifetime. It stresses the urgency of the problem related to improvement of a future music teacher’s readiness to self-education by means of modern informational technologies (IT). The article deals closely with the process of professional training and forming readiness to self-education in future music teachers relying on their informational and communicative competence. The present scientific statements on arranging self-education have been considered. The article determines informational and communicative competence and "self-education by means of music computer technologies" aimed at improving abilities for music, bringing up a socially active personality and developing art skills of electronic music making (composing, sound managing , performing). The article is aimed at developing a methodical model of forming readiness to self-educational activities in future music teachers by means of informational technologies. The leading method is the method of modelling of self-education by means of IT in the pedagogical university as a targeted and organized process of improving a future music teacher professional training components required for the efficient professional activity. The present model structure includes motivational, meaningful, operational and reflexive components.
Heating and Cooling of Food

As we have seen, heating of food is one of the oldest and most powerful ways of making food safe and stable, whether cooking a burger on a barbecue or pasteurizing juice, but is also a potentially highly damaging thing to do to many food products. So, it makes sense that a key principle of processing food is to understand how to control the flow of heat as precisely as possible. In Chapter 8, I introduced how we can maximize the efficient transfer of heat into and out of food in a kitchen in simple systems, like pots on stoves. In practice, in large-scale processes, to transfer heat efficiently from hot to cold, and in this way keep the lords of thermodynamics happy while minimizing damage to the food being heated, we need to use clever pieces of equipment, called heat exchangers (reflecting the fact that, just as the cold part of the system gets hotter, so the hot part gets colder in the deal; fair exchange is no robbery). To visualize a heat exchanger, imagine a simple metal tube, through which a cold liquid is flowing from one end to the other. Now surround that tube with a larger one, through which a hot liquid flows (as shown in Figure 11.1). The wall of the inner tube is exposed to cold on the inside and hot on the outside, and this temperature gradient is the pump that transfers heat across that wall, in nature’s obsessive quest for equality in all things temperature-y. So, now we have two tubes laid horizontally in concentric neatness, say with a hot and a cold liquid flowing in from the left-hand side; as they exit at the right-hand side, the outer hot liquid will be colder, and the inner liquid will have gained the lost heat and thus become hotter. If the tubes were sufficiently long, then both would come out at exactly the same temperature.
Determination of a coefficient of thermal expansion by machine learning

Objective of this work is to model the thermal expansion coefficients of selected steel grade and compare results with those measured by TMA method.Coefficient of thermal expansion is described as a function of steel composition (C, Mn, P, S, Si, Cr, Ni, Mo) and temperature.Experimental values are described and compared with model.Correlation analysis of these data sets is done.Presented model is based on using artificial neural network and represents a preliminary test of method capability to be used for such problems classfor predicting of thermophysical properties depending on composition and temperatre.
Latent Template Induction with Gumbel-CRFs

Learning to control the structure of sentences is a challenging problem in text generation. Existing work either relies on simple deterministic approaches or RL-based hard structures. We explore the use of structured variational autoencoders to infer latent templates for sentence generation using a soft, continuous relaxation in order to utilize reparameterization for training. Specifically, we propose a Gumbel-CRF, a continuous relaxation of the CRF sampling algorithm using a relaxed Forward-Filtering Backward-Sampling (FFBS) approach. As a reparameterized gradient estimator, the Gumbel-CRF gives more stable gradients than score-function based estimators. As a structured inference network, we show that it learns interpretable templates during training, which allows us to control the decoder during testing. We demonstrate the effectiveness of our methods with experiments on data-to-text generation and unsupervised paraphrase generation.
Estimating solar radiation in a clear sky on a horizontal surface from common meteorological a data in Oran, Algeria

This study aimed to calibrate existing model (Platt and Paltridge model) and develop a new models for estimating the different components of the solar radiation on a horizontal surface in a clear sky data using commonly and available measured meteorological records such as water vapor tension and temperature, etc. Four models based on meteorological variables were generated and validated using daily data in 2013-2016 at the Oran Station (Algeria). Validation criteria included coefficient of determination, root mean square error and mean bias error, the results showed that the proposed models can estimate solar radiation values. The model based on the temperature and the water vapor tension gives better results with statistical errors obtained are as follows: NDMBE = 13.36 %, NDRMSE = 47.08 % and the correlation coefficient R = 0.85 for the diffused component, the model based on relative humidity and atmospheric pressure gives better results for the direct component with statistical errors obtained are: NDMBE = -1.54 %, NDRMSE = 22.59 % and the correlation coefficient R = 0.95 and The model based on the relative humidity and the water vapor tension with results: NDMBE = 0.96 %, NDRMSE = 12.08 % and the correlation coefficient R = 0.98 for the global component.
Steps towards autonomous driving: deep semantic segmentation among weather conditions

Nowadays the machine learning algorithms and more in general the artificial intelligence have become crucial in the scientific development, there are a lot of new research fields involved in this subject and this topic is highly correlated to every environment. One particular application on which this thesis is focused is autonomous driving. A very important field involved in this topic is computer vision. In this case the goal is to become capable to understand every part of the image, being able to distinguish between the different areas of the picture (i.e. which part of the view is the street, which part is a sidewalk, or if there is a traffic sign). This branch of computer vision based on neural networks is called semantic segmentation and it’s very useful but extremely hard to train due to the lack of data. In fact, to train a simple network for image recognition, we must provide a set of training images labeled as the subject while in this case a label for each pixel of the image is needed, to allow the network to become more and more precise. This type of labeling is hard and extremely time expensive, so a possible solution are synthetic datasets, generated by simulators that can automatically assign to every pixel a label, being very precise and low time consuming, but with the disadvantage to have less realistic images. Up to now, there aren’t a lot of this datasets for the training of networks for autonomous driving, and it is one of the main reasons for this work. In this thesis, the objective is to describe the newly created dataset IDDA - ItalDesign Dataset, that has been thought to address this problem. In fact, it contains a lot of different conditions well-separed in order to perform these types of trainings. It is based on the CARLA simulator, and with it we generated over one million images, with different conditions of weather, vehicle point of view and town. After that, we tried a state-of-the-art network (ADVENT) with our dataset, in order to try to understand how it performs on the domain shift generated by the weather conditions change.
Research Guides: PAF 3015: Qualitative Studies of Communities - Fall 2020 - Prof. Balboa: Finding E-Books

Newman library resources, and other suggested resources to research communities that students have selected.
Blockchain, Digital Identity and Health Records: Considerations for Vulnerable Populations in California

Author(s): Crittenden, Camille; Sistla, Maitreyi | Abstract: This report explores the overall potential of blockchain’s use in the public sector and focuses on two use cases that have received less attention: blockchain-based digital identity and health records management systems for the homeless and other vulnerable populations in California.
Teacher Training For Educational Achievements Diagnosis And Evaluation: Approaches And Tools

One of the urgent tasks that characterize national educational systems of the world is to ensure the result that meets expectations of the family, modern society, state and suits the conditions of the global economy and competition. Unified approaches to designing and providing results lead to increased attention to the development of procedures for their measurement and evaluation, creation of national systems for verification and evaluation of educational results that meet global trends in education. The success of these tasks is directly related to the problem of teacher training. The purpose of this paper is to characterize and analyze the state of modern practice of organization of educational achievements diagnosis and evaluation as an indicator of deficiencies in teacher training and to describe the proposed educational module to overcome the identified deficiencies. Materials of the article contain the results of the study related to identification and testing of organizational and pedagogical conditions that ensure teachers' preparedness for diagnosis and evaluation of educational results in accordance with the conceptual provisions of the national system of evaluation of educational achievements. The leading theoretical methods of research include analysis of normative and scientific literature on the problem, systemization, specification, interpretation; the empirical ones are methods of questioning, survey, processing and statistics analysis were used. The article substantiates the correlation between educational results of schools students and the practice of organization of educational achievements verification and evaluation; describes the organizational and pedagogical conditions of training future teachers for diagnosis and evaluation of educational results.
Distributed quantum computation – how does it scale?

We explore the concept of distributed quantum computation, discussing the advantages and disadvantages of this approach. We divide its development into three layers and highlight the challenges we face in each stage. With a few examples we explore the scalability of such disturbed quantum systems. © 2020 The Author(s)
Retraction: Machine learning algorithms for prediction of dyslexia using eye movement (J. Phys.: Conf. Ser. 1427 012012)

This article has been retracted by IOP Publishing on 06 November 2020 due to plagiarism from "Automatic detection of developmental dyslexia from eye movement data" (the "original work"), Peter Raatikainen, Master's Thesis in Information Technology, 2019 https://jyx.jyu.fi/bitstream/handle/123456789/64482/URN%3aNBN%3afi%3ajyu-201906103105.pdf?sequence=1%26isAllowed=y . The original author's supervisor notified IOP Publishing of this issue on 29th October 2020 and alerted the Publisher of the issue. IOP Publishing has investigated and agrees that the IOP Publishing article has inappropriately used ideas, content and figures from the original work. The authors of the IOP Publishing article have confirmed the inappropriate use of the content and they agree to this retraction. Retraction published: 06 November 2020
E-Educational Content Designing And Its Introduction In Group Activity Clubs

In the context of implementation of the information society development strategy and the concept of the school additional education development the main priority is to develop and improve the electronic education process and to use it in the school additional education system. One of the popular forms of additional education is a group activity club with the use of e-learning technologies. The development of electronic group activity is not only the purpose of education, but it is also a means of effective implementation of innovative educational programs. Organization and implementation of the electronic group activity strategy requires competent staff, legal support, educational program support that includes the electronic educational content development, technical and technological support. The electronic educational content is one of the key elements in the organization and implementation of group activity with the use e-learning technologies. There are specific conditions and procedure of e-educational content development. This article deals with the problem of designing and development of electronic educational content that will help to organize and implement the group activity strategy using e-learning technologies; describes the components of electronic educational content. The article focuses on the problem of special teacher training in content development and its application in the educational process. The article provides intermediate results of the research project – “Development and Implementation of the Group Activity Model That Provides a Student with Practical Training with the Use of E-learning Technologies (various exercises, simulators) and Builds a Relevant Material Database”.
The Advantages of Personal Documentation Video in Improving Students’ Speaking Skill for Presentation

Speaking is one of the most important skills in English.Speaking English in public is difficult for Indonesian students because English is learnt as foreign language.Speaking practice should be done continually and effectively.Personal presentation is used as a practice method for students to be able to speak in public.By combining digital technology and education, the objectives of this study are (1) classifying the time allotment of personal documentation video done by students; (2) describing the topics of personal documentation video done by students; (3) describing the speaking problems faced by students; and (4) classifying the advantages of students by composing personal documentation video.This descriptive qualitative study analyzed data in the form of speaking recorded in video projects done by students and interviewed result with the students.After classifying the data based on the duration of the videos, it was found that there are 21 videos (25,30%) which have duration less than 7 minutes, 52 videos (62,65%) which fulfill the duration requirement in 7 -10 minutes, and there are 10 videos (12,05%) which have more than 10 minutes duration.It shows students' vocabulary mastery in describing something.The common topics used by students in the project were hometown, hobbies, describing things, and tourism or travel experiences.This study found that the common problem in speaking is the lack of confidence caused by the lack of vocabulary, grammar, fluency and pronunciation.This study also finds the advantages of students' developments in speaking skill for presentation after composing personal documentation video project.
Checking library collection enables to analyze its composition as exemplified by the Pushkin State Museum of Fine Arts Research Library

The Library of the Pushkin State Museum of Fine Arts is rich in rare and unique publications, and those of memorial value. The collection checking envisages visual revision and analysis of every book, and during this process the specialists revealed a number of valuable publications for further research. Also all registered publication went through the stage of initial collection specification (e.g., Rumyantsev museum collection, collection of the New Western Arts Museum, memorial libraries, etc). Currently, this information has been being entered into the e-catalog. This will enable to verify special arrays within the Research Library’s collection and simplify investigations into historical and memorial book collections and individual valuable publications.
Code Reviewer Recommendation : A Context-Aware Hybrid Approach

Background. Code reviewing is a commonly used practice in software development. It refers to the process of reviewing new code changes, commonly before they aremerged with the code base. However, i ...
4차 산업혁명 시대의 역사교육 - 대학 역사교육에서 ‘역사하기(Doing History)’ 컨셉 활용하기 -

The Fourth Industrial Revolution is written big in all kinds of discussion about economic innovation as well as educational reform. Often speculated is the Fourth Industrial Revolution’s tremendous speed of development and its formidable power of transformation. Instead of exaggerating and speculating the destructive potential of the revolution, this paper will pay special attention to the conspicuous moves of IT giants like Apple, Microsoft, or Google to invest in educational businesses, and pose the question ‘why education?’.Starting from this question, the history of Industrial Revolution from the First through the Third is revisited, highlighting the education-led feature of the Second Industrial Revolution. If the high education played a decisive role in the Second Industrial Revolution, even more significant role of education is expected for the era of the Fourth Industrial Revolution, facing the rise of Homo Deus equipped with a unprecedentedly advanced technology. In order to cope with the problems caused by the Fourth Industrial Revolution and Homo Deus, innovated education for a creatively and deliberately thinking citizen is desperately needed.This paper critically reviews the Doing History concept as the most promising didactic methodological concept for drawing realistic lessons for innovating history education in Korea. Taking into account the limited conditions of history classes at Korean universities, the possibility of applying Doing History to lecture-led classrooms is more actively discussed.
On Log-Loss Scores and (No) Privacy

A common metric for assessing the performance of binary classifiers is the Log-Loss score, which is a real number indicating the cross entropy distance between the predicted distribution over the labels and the true distribution (a point distribution defined by the ground truth labels).In this paper, we show that a malicious modeler, upon obtaining access to the Log-Loss scores on its predictions, can exploit this information to infer all the ground truth labels of arbitrary test datasets with full accuracy.We provide an efficient algorithm to perform this inference.A particularly interesting application where this attack can be exploited is to breach privacy in the setting of Membership Inference Attacks.These attacks exploit the vulnerabilities of exposing models trained on customer data to queries made by an adversary.Privacy auditing tools for measuring leakage from sensitive datasets assess the total privacy leakage based on the adversary's predictions for datapoint membership.An instance of the proposed attack can hence, cause complete membership privacy breach, obviating any attack model training or access to side knowledge with the adversary.Moreover, our algorithm is agnostic to the model under attack and hence, enables perfect membership inference even for models that do not memorize or overfit.In particular, our observations provide insight into the extent of information leakage from statistical aggregates and how they can be exploited.
The impact of COVID-19 on people with diabetes in Brazil. (Special issue on diabetes and COVID-19: the IDF perspective.)

The present study aims at identifying main barriers faced by people living with diabetes in Brazil during the COVID-19 pandemic