Reviewerly/exHarmony huggingface dataset:
Vehicle Re-identification Based on Dual Distance Center Loss

Recently, deep learning has been widely used in the field of vehicle re-identification. When training a deep model, softmax loss is usually used as a supervision tool. However, the softmax loss performs well for closed-set tasks, but not very well for open-set tasks. In this paper, we sum up five shortcomings of center loss and solved all of them by proposing a dual distance center loss (DDCL). Especially we solve the shortcoming that center loss must combine with the softmax loss to supervise training the model, which provides us with a new perspective to examine the center loss. In addition, we verify the inconsistency between the proposed DDCL and softmax loss in the feature space, which makes the center loss no longer be limited by the softmax loss in the feature space after removing the softmax loss. To be specifically, we add the Pearson distance on the basis of the Euclidean distance to the same center, which makes all features of the same class be confined to the intersection of a hypersphere and a hypercube in the feature space. The proposed Pearson distance strengthens the intra-class compactness of the center loss and enhances the generalization ability of center loss. Moreover, by designing a Euclidean distance threshold between all center pairs, which not only strengthens the inter-class separability of center loss, but also makes the center loss (or DDCL) works well without the combination of softmax loss. We apply DDCL in the field of vehicle re-identification named VeRi-776 dataset and VehicleID dataset. And in order to verify its good generalization ability, we also verify it in two datasets commonly used in the field of person re-identification named MSMT17 dataset and Market1501 dataset.
Medicine Image Data Abstraction Using Image Processing

In order to show signs of improvement recuperation and maintain a strategic distance from any reactions it is significant that the patient should take right drug for the affliction is they are enduring with. Medication data on names is a noteworthy wellspring of learning for patients. This is the significant part of prescription however we are discovering numerous cases wherein the incorrect data about the medication may make terrible effects on the individuals and will in general broaden numerous issues as opposed to decreasing the ailment. The fundamental explanation behind this, is absence of data about the medication to the patient and some being ignorant or mind conviction on the medications. In order to defeat this issue medicine data abstraction using image processing is an application which causes you to see the medication dependent on the manifestations to which the prescription is to be utilized at anyplace, whenever, through your cell phone. It encourages you to get the data of the drug by simply sitting at your home and snapping the photo of the medication.
Motivational and cognitive value of games in the teaching process

It has long been recognized that learning content is very useful for developing the intellectual and creative abilities of children. Modern teaching requires dynamic, diverse teaching and its adaptability to the abilities of each individual student. This implies a skillful combination of modern teaching materials, methods, forms and the choice of teaching form in each lesson. In that context, motivational games in the class have a special function. It is common knowledge of every teacher that students in classes need to be encouraged towards full engagement of cognitive abilities. This is not always easy to achieve. In every class, psychological preparation (application) is necessary to mobilize students' attention in the shortest possible period of time, prepare them for cognitive activities, whether it is preparation for the processing of new teaching contents, doing exercises or repeating old material. In all this, well selected motivational games can play a significant role. With engagement of cognitive process in solving such tasks, students can find successful solutions in a short time, and success is the best motive for further work in class.
Can Privacy-Preserving Machine Learning Overcome Data-Sharing Worries?

Data volumes are exploding faster than our ability to interpret or secure them. Can techniques such as privacy-preserving machine learning address those challenges?
TEACHING ENGLISH VOCABULARY ACQUISTION THROUGH GESTURE

Abstract: Teaching vocabulary has been integrated in four skills: listening, speaking, reading, and writing. Most of the students always got low mark in the English test. After the researcher interviewed them, the problem was that they do not understand about the meaning of the vocabularies in the text. This research was literature study. The main objective of this research was to explain how far the strategy of using Gesture. The data in this study were collected through observation, documentation book, journal, and internet. Based on the data analyzed, it can be concluded that gesture can be applied in teaching vocabulary. There are four categories using gesture; 1) Iconic Gesture; 2) Metaphoric Gesture; 3)Deictic Gesture; 4) Beat Gesture.
The Application of the Model of High-Speed Pixel Clustering in Problems of Preprocessing of the Images of the Remote Sensing of the Earth

The purpose of the research is to use the modified Ward’s method in high-speed processing of full-HD images of the remote sensing of the Earth. The classical Ward’s method is modified by dividing the computational process into three successive stages. The first stage quickly builds a coarse hierarchy of approximations. The second stage performs a quality improvement of the specified partition for a fixed number of colors (clusters). The third stage is the clustering of the superpixels using the Ward’s method. The software-algorithmic toolkit consists of four operations on clusters of pixels and image segments: merge operation joins together two clusters; divide operation reversibly disjoins the selected cluster into two; split operation extracts the part of the cluster into individual cluster; correct operation reclassifies pixels by extracting from one cluster and inserting into another cluster. The quality is assessed by the total squared error. The quality improvement is provided by iterative execution of a combination of merge and divide operations of pixel clusters, in particular image segments. One of the clusters (segments) is divided in two and a pair of other mismatched with it is combined into one according to the criterion of the minimum increment of the total squared error. The proposed modified Ward’s method is appropriate in processing of fullHD images of the remote sensing of the Earth. The results of processing in pure segmentation and clustering modes are compared. The proposed pixel clustering model is appropriate in high-speed processing of the fullHD images. The pixel clustering in comparison with image segmentation allows to define in more detail both the contours of objects of interest and their internal structure
USER’S OPINIONS ON ANDROID-BASED LEARNING

The purpose of this research is to find out the user's response to e-module based on android products to facilitate learning process. Likert scale with four variations of the answer was the scale used in this study. Research data were analyzed by quantitative descriptive. The result of the research showed that e-module based on android products have met the eligibility criteria with the category "very good" so it is worth to use. The data of the research showed that User’s response to e-module in this case teachers and students obtained “very good” category with the feasibility percentage of each are 84.38% and 81.67%.
Diagnostic Evaluation Application as Requirement on Course Beginning for First Baccalaureate "a" Sciences on Educational Unit "El Carmen"

This paper analyzes the application of diagnostic evaluation, a requirement at the beginning of the course in the First Baccalaureate A, Sciences in the Educational Unit El Carmen, using as a methodology the survey focused on students of the first baccalaureate, obtaining in this institution that if they carry out a 100% diagnostic evaluation, using the written test as a format, with closed questions, making the respective feedback and generating in students the knowledge of the importance of said evaluation for their formative process. Therefore, it has concluded that teachers are doing on time and using a good evaluation format with students.
Comparing Different Models for Credit Card Fraud Detection

This paper incorporates the Credit Card Fraud Detection models to study and identify legitimate and fraud transactions.This research intends to recognize the false transactions while avoiding incorrect fraud classifications.The informational collection or dataset (Credit Card Fraud Detection) utilized in the proposed work is given by Kaggle which can be at https://www.kaggle.com/mlg-ulb/creditcardfraud.Before uploading on the website (Kaggle.com),these features are renamed and re-defined as PCA (Principal Component Analysis).There are general features in which 28 out of them are renamed as V1 through V28 (all numeric qualities).Rest three of the features showcase the time, calculated amount and whether that transaction was fraudulent or not.The response variable is 1 for a false transaction and 0 for a safe transaction.The chosen data set does not contain missing qualities.The dataset contains 284,807 transactions in which most of the transactions are very small and very few of the transactions come even closer to the maximum.Different algorithms are implemented in this study.Python Machine Learning libraries are used to perform those algorithms.The model studied in this research work are K-Nearest Neighbour, logistic regression, random forest model, XGBoost model.As the XGBoost is showing more accuracy than other models.Out of these algorithms, XGBoost model is preferable over the Random Forest model and Logistic Regression model.
Navigating the Road to Successfully Manage a Large-Scale Research and Development Project: The Exascale Computing Project (ECP) Experience

The road to successful management of a large research and development (R&D) project requires comprehensive and flexible capabilities to foster effective and timely communication, tracking, and decision-making. Best practices developed and employed by the Exascale Computing Project (ECP) afford a comprehensive example of management practices that benefit this type of a large-scale, physically dispersed R&D project. This article will summarize the ECP’s hybrid approach to project management, which incorporates principles of the Department of Energy (DOE) order for the management of large capital asset projects (DOE O 413.3b) and elements of industry-standard Agile practices, as well as the tools that promote extensive collaborative endeavors. Using a hybrid approach to managing project elements is a key tenet within the ECP and is implemented in part by ensuring that information such as detailed technical plans and achievements, budget and cost information, milestone creation, and progress metrics are readily accessible to all participants. The functionality to enable this broad, dynamic access is provided by a variety of essential and flexible tools, which the ECP has found to be invaluable in managing work and communicating with project team members and stakeholders. The strong integration of R&D efforts results in a dynamic environment in which frequent input from management, collaborators, and stakeholders is essential. This overall approach provides the guidelines and policies, processes, information, tools and services, and output that are necessary for the effective management of large, complex projects. Such an approach may also be applied to smaller, less complex projects for a similar outcome.
OPTIMALISASI PENGGUNAAN E-MODUL DAN PHET SIMULATION SEBAGAI VIRTUAL LAB DI MASA PANDEMI COVID-19

This study examines the use of e-modules and PhET simulations as virtual labs in basic physics. The purpose of this research is to optimize the available virtual labs. To facilitate the implementation of practicum, this study uses e-module as a companion material used by users. The research was conducted in two stages. The first is conducting direct trials using PhET simulations and e-modules through Google classroom. The second stage is primary data collection through a questionnaire instrument given to respondents via Google form. The questionnaire instrument was then analyzed by testing the validity, reliability and usability. From the validity and reliability test results obtained 9 question items that have valid and reliable criteria of 0.936 with very high criteria. The usability results show the percentage of respondents to the questions given through the questionnaire dominated by agreeing and strongly agreeing to the four usability factors. This shows that the use of e-module and PhET simulation as virtual lab fulfills the usability element.
PHYSICS COMPREHENSIVE CONTEXTUAL TEACHING MATERIAL UNTUK MENINGKATKAN KEMAMPUAN ARGUMENTASI

Contextual Teaching Learning (CTL) is learning based on contextual events in daily life. The development of teaching materials assisted by android applications in learning physics is a very necessary thing and needs to be carried out continuously. This research aims to produce android-assisted PhyCCTM teaching materials that can improve the ability of argumentation. This research is research and development. The development procedure refers to the development model adapted from the 4D model which consists of four stages namely defining, designing, developing, and distributing. Content validation was carried out by four lecturers and seven physics teachers. Field trials are carried out in schools by applying the quasi-experimental method and using the control group pretest and posttest design. The trial was conducted by taking two classes as experimental and control classes. Improvement and differences in the results of students' argumentation abilities in the experimental and control groups were done by t-test. The research results obtained are android-assisted PhyCCTM teaching materials to improve the ability of argumentation worthy to be used with the category of "Good" and android-assisted PhyCCTM able to improve students' ability to argue with sig. (2-tailed) of 0,000. The conclusion obtained from this study is that Android-assisted PhyCCTM teaching materials developed are feasible to use and are able to improve students' ability to argue.
PEMANFAATAN SARANA TEMU KEMBALI INFORMASI DI PERPUSTAKAAN UNIVERSITAS BUNG HATTA

The means of retrieval of information owned by the library at Bung Hatta University is OPAC, a facility that implements an online system, this facility is one or several computers (PCs) provided by the library which can be used by all users to browse the library catalog which is already in the form of a base. electronic data. Online public access catalog (OPAC) basically provides more benefits in recovering information in the library. the use of information retrieval facilities by library users at Bung Hatta University by using needs, motives and interests. OPAC is known to some users at Bung Hatta Library from searching the internet and asking friends. The motive of students using OPAC is to get the collection of books they are looking for. on the indicator of interest in using OPAC facilities, namely to facilitate information retrieval.
SIGACT News Complexity Theory Column 107

Warmest thanks to Mark Bun and Justin Thaler for their terri c article, \Approximate Degree in Classical and Quantum Computing." And, amazingly, they made the time to craft it during a time of worldwide pandemic|wow!
APLIKASI PEMASARAN DAN PENJUALAN KARANGAN BUNGA BERBASIS WEBSITE MENGGUNAKAN METODE FIFO PADA CV. DIKREZ FLORIST

This research was conducted at the company CV. Dikrez Florist, this company is engaged in the sale of bouquets. Problems with CV. Dikrez Florist is sales of flower bouquets every year there is less increase and sales turnover has also decreased, because the marketing system is not optimal, because customers who order lots of flower bouquets are customers in the company area, while the wider community does not know the location or whereabouts of the company Then, if the customer wants to order a flower bouquet, he must come to the company. As well as processing sales data using simple notes using books. For this reason, it is necessary to make a website-based marketing and sales application of wreaths using the FIFO method so that the marketing system and sales of flower bouquets can be increased, and computerized processing of sales data. The research method used is SDLC with the waterfall model where the stages are analysis, design, coding and testing, and using the FIFO method in making flower bouquet sales reports. The results obtained from this study are in the form of a website-based marketing and sales application of flower arrangements using the FIFO method.
Symmetry Implies Isomorphism for Certain Maximum Length Circuit Codes

A classic result due to Douglas establishes that, for odd spread $k$ and dimension $d=\frac{1}{2}(3k+3)$, all maximum length $(d,k)$ circuit codes are isomorphic. Using a recent result of Byrnes we extend Douglas's theorem to prove that, for $k$ even $\ge 4$ and $d=\frac{1}{2}(3k+4)$, all maximum length symmetric $(d,k)$ circuit codes are isomorphic.
PROFESSIONAL PORTRAIT OF A SUPERVISOR OF A REGIONAL UNIVERSITY MASTER’S PROGRAM

Statement of the problem and purpose of the article. An increase in the number of master’s programs, the problem of sustainable development of students, the attraction of employers, the introduction of modern teaching technologies actualizes the management of educational programs. The article examines the problem of personnel and academic leadership of supervisors of master’s programs in regional universities in order to determine their distinguishing socio-demographic and professional characteristics. The research methodology is based on conceptual works to study the mission of a modern university, academic leadership and human resources, principles of master’s programs design based on learning outcomes. Professional and socio-demographic characteristics were studied using a questionnaire survey of academic staff from 16 regional universities. As a result of a comparative analysis, a professional portrait of the program supervisor was compiled. Research results. The socio-demographic and professional characteristics of supervisors of different types of programs that distinguish them from an academic staff are revealed. It is shown that supervisors are characterized by a combination of research and training, the priorities of which vary depending on the type of programs; participation in the development of educational programs. Differences are noted depending on the type of a program: academic or applied. Conclusion. A supervisor of master’s program becomes one of the key factors in the development of the master’s program, the activity of which determines the need to develop special mechanisms for management support.
Machine Learning Models Under the Copyright Microscope: Is EU Copyright Fit for Purpose?

This paper is based on a presentation given in December 2019 at the Lund’s University conference Artificial Intelligence (AI), Data Protection and Intellectual Property in a European context. The purpose of this article is to analyse the suitability of the copyright system over the so-called of Machine Learning (ML) systems, the ML models. Computer programs protection has always caused certain difficulties for intellectual property law. Internationally is was agreed in the 1970s to protect computer programs as literary works of copyright. ML models have been called computer programs, super-software. Yet, unanimity lacks as to technically agree on what they are. This is relevant from a copyright perspective, because depending on whether the ML model qualifies as a computer program, as a mathematical method or as another type of work, the regime of protection granted by copyright will be different. Additionally, all proprietary and open-source software licensing relies on the copyright protection. In most open licenses, if the license is applied to something that is not protected by copyright (or related rights) the license is not triggered. Thus, it seems relevant to question whether EU copyright law provides adequate protection for the core components of machine learning systems, the ML models. This paper begins with an overview of justifications for copyright protection of computer programs. Understanding how this came about is important to consider protection insufficiencies and how this can later be applied to ML models. It follows a technical overview of the differences between AI software, ML models and algorithms, as to delineate and frame the type of work that a ML model would be. This part also focuses on the differences between traditional (non-AI) software and ML process design and development, and the role that ML models play therein. The third part explains what the legal framework for copyright protection of computer programs is and tests its applicability to ML models. The paper is finalized with a set of conclusions and thoughts for future reflection.
APPLICATION OF CASE TASKS IN THE ASSESSMENT OF PROFESSIONAL COMPETENCE OF A FUTURE TEACHER

The introduction of a new model of certification of teachers in Russian Federation, based on the implementation of the principles of the activity approach in pedagogical practice, as well as the requirements for applying professional actions in the course of pedagogical work, determines the problems of assessing the level of formation of professional competencies among graduates of pedagogical universities. To assess the pedagogical skills of students, it is necessary to determine (operationalize) those indicators that would reveal the compliance of the performed actions with the requirements of the Federal State Educational Standards and the Professional Teacher Standard.
WAY TO SMART LIFE USING DATA MINING

Information offers numerous prerequisites to the end clients, for example, programming, association and stage go on. In this proposed framework, we concentrate about carefully mining the information on social media. Online media turns out to be well known from the information given by biomedical and other providers. This data is usually shared so that medical service improves, costs declines and utilises the assessment which is created by client. We suggest investigation framework that give attentions on side effects of drugs and also focus on positive and negative response. To improve health care some Clinical documents are mostly useful because these are free text data sources. Clinical reports containing data identified with manifestations and significant meds. Extracting data from enormous dataset became famous in light of the fact that clients get different thoughts from this shifted information. Data Mining and Knowledge mining became well known on the grounds that clients are aware of information and getting data of various region like wellbeing, Social, etc. After information preparing we center on clients positive and negative assessments. We exclude these feelings and discover which prescription is great; to choose this we additionally discover the symptoms of the drugs. Further we center on the manifestations of the sickness of tolerant. By taking the master specialists proposal, we rattle off the medicine of any sickness as per the side effects and we give this medicine or treatment to the client on our gathering. We can grow our examination into Data and Knowledge mining of online media and takes the client’s reviews on different medications of Illness. This day by day refreshed information serves to drug industry, specialists, emergency clinics, and clinical staff, for viable future medicines. KEYWORDS: Information mining, Complex organizations, social figuring, Data mining, semantic Web.