Reviewerly/exHarmony huggingface dataset:
Support Vector Machines in Smile detection: A comparison of auto-tuning standard processes in Gaussian kernel

Support Vector Machines are a set of machine learning models that have great performance in several tasks as well as on image classification and object recognition. However, the proper choice of model's hyperparameters has a great influence on the outcomes and the general capacity performance. In this paper, we explore some different traditional auto-tuning processes to estimate σ hyper-parameter for SVMs Gaussian kernel. These processes are common and also implemented on standard software of data science languages. The paper considers some different situations on smile detection. The results are composed by simulation study, two benchmark image applications and a real video data application.
A CAPSTONE PROJECT IN SOFTWARE DEVELOPMENT FOR CIS MAJORS

This paper presents a capstone project given to CIS seniors utilizing programming, database design, requirements analysis, use case, and object modeling, project management, and writing and oral communication skills in an active learning environment.The learning objectives for this project corresponds with most of the learning units described for the upper level courses in the IS 2002 model curriculum and is based on an object-oriented methodology that centers on component-based design.Students also engage in reflective analysis by constructing project workbooks and journals.
Analysis of Student’s Difficulties on Generalizing Linear Equation

One of the essential aspects of reasoning mastered by students is generalization.By learning generalization type mathematical abstraction skills, students can provide arguments or conclusions based on facts from the relationships between the rules found.This type of research is a descriptive study that aims to describe the generalization ability of the material on straight-line equations through the CPS learning model assisted by learning videos.The instrument uses the Creative Problem Solving learning model and is administered by teaching videos.The instrument is in the form of written test questions regarding the material of straight-line equations and interview guidelines to measure the generalization ability of students.What will analyze the results of the tests and interviews to get a conclusion.
Development and Exploration of Potassium Sulfate Preparation Experiment Guided by Quaternary Phase Diagrams in Undergraduate Experimental Teaching

The preparation of potassium sulfate using a two-step method is an important method for the large-scale production of potassium fertilizer.Our experiment uses it as a reference, taking the basic knowledge of the quaternary phase diagram as the theoretical guideline, and covers the relevant knowledge of inorganic double decomposition reactions and element ion analysis detection.In this study, we use a combination of testing methods including traditional titration, spectrophotometry, and ICP atomic emission.This promotes basic operational knowledge and theory, as well as a combination of traditional and modern instrumental analysis.The experiment has many advantages, such as easily obtainable materials, easy operation, obvious phenomena, and green environmental protection.It can be used in modular teaching and divided into multiple experimental links to meet the requirements of different students.The operation of the experiment can not only make students realize the important role of chemistry in social production but also cultivate their basic operational ability and improve their basic practice and innovation ability.
Identification of Higher Order Thinking Skill Domain in The Eleventh Grade English Lesson Plan at SMK N 1 Singaraja

This research aimed to identify the cognitive domains of Higher Order Thinking Skills that appear in the four English Lesson Plans in eleventh grade and the most dominant cognitive domain of Higher Order Thinking Skill used in the four English lesson plans in eleventh grade. This research used descriptive qualitative research design. The setting of this research is in SMK N 1 Singaraja. The subject of this research were the English lesson plans and one of the teachers in SMK N 1 Singaraja. The data were collected by using documentation, checklist, and interview guide. The results of this research are, (1) There are two cognitive domains (C4 &amp; C6) appear in those four lesson plans, (2) The most cognitive domain appear in the four English lesson plans is C6 with the operational verb is arrange.
Consumption coordination control method of distributed clean power supply under load balancing

Aiming at the problems of large control error and long time-consuming in the traditional power consumption control method, a new distributed clean power consumption coordination control method under load balancing is proposed. Based on the analysis of load balancing, the distributed clean power generation is preprocessed to determine the consumption constraints of distributed clean power generation. Using the weighted summation method, the complex multi-objective optimization solution is equivalent to a single objective optimization problem to realize the consumption coordination control of distributed clean power generation. The experimental results show that when the control quantity is certain, the control error of the improved method is reduced by about 11.01% and 5.18%, the control time is reduced by about 3.94s and 15.27s respectively, which has certain research significance.
Research on Innovation of Junior Middle School PE Teaching Mode Based on WeChat Platform

Junior middle school physical education is an essential teaching project, physical education can maintain a healthy state of mind, improve confidence and values, enhance the spirit of sports, improve the overall physical quality.The teaching effect has a great influence on students, from small to sports skills, to the physical and mental development of students.With the rise of "WeChat platform teaching model", many experts began to carry out certain studies in some schools and achieved certain results.Most of the teaching modes with the help of "WeChat platform" are based on cultural courses such as language, mathematics and English, and there are few cases of using it in physical education teaching mode.This study is to combine WeChat platform with junior middle school physical education, analyze the current situation of junior middle school Physical education, analyze the shortcomings of traditional junior middle school physical education teaching, and try to use modern WeChat platform to innovate teaching mode in physical education class.Literature, logical analysis and interview were used in the study.Then, according to the advantages and characteristics of WeChat platform and the research on the innovation of junior middle school PE teaching mode, a new "one-to-one teaching mode, platform group mode and program competition mode" is created to stimulate students' enthusiasm and achieve certain teaching objectives.Through analysis and research, it is concluded that: 1) Junior high school students have a high acceptance of this teaching mode on WeChat platform.Improving students' attitude towards sports can fully mobilize their enthusiasm and active participation in learning.2) The new sports teaching mode on WeChat platform increases the interaction between teachers and students and improves students' mastery of sports skills.3) It is feasible to use the sports teaching mode of WeChat platform.
Stability of artificial intelligence controlled systems

The impact of artificial intelligence in novel design of system of systems is substantially increasing, having influenced overall behavioral pattern of full setup. Major impact could be seen in large systems equipped even with minimum artificial intelligence elements up to specifically designed systems e.g. for evaluation of contribution on social network. The basic characteristic of any artificial intelligence program is that creator cannot predict next steps in the behavior of the whole system controlled by artificial intelligence. It can be done only based on statistical estimation, because real artificial intelligence program cannot behave deterministically. Moreover, the artificial intelligence programs today are not capable to demonstrate such a quality as intuition or deep abstraction etc., which are specific to human. The concentration of the cyber systems as are sensor and actuators network in IoT environment or autonomous car groups under control of artificial intelligence of the similar design can be source of instability of the system itself.When we talk about a system stability, we usually consider the system with some observable feedback and short control loops. In the large system of systems, the control loops are multiple, hidden and mutually affected. In our contribution we are going to show the possible way of analysis of such a case of dynamic system behavior based of semidefinite programming approach for both linear and non-linear system with and without feedback loop. Naturally, where the feedback loop will be missing, the stability of the system will be very sensible to border conditions while in the case of very tight loop the system will be kept to one specific state. Both of these marginal solutions are not acceptable for large systems equipped with artificial intelligence.The goal of system of systems equipped with artificial intelligence would consist in ability to cover very large number of possible states, often vaguely defined, based on probability of the border conditions. The system of systems remains in the state achieved, analyzing its state itself and implementing change into another state under reasonable change in the environment. So it means system of systems will remain in the probabilistically optimal state until the self-analysis will show necessity to change this state to another, more optimal, state. But change in the state can lead to instability of the system of systems when probabilistic estimation will fail or environmental condition are not in the form known from the past. Based on this analysis we expect to show, that system of systems, where the internal systems are using artificial intelligence, could be statistically stable only. Hereto such a system could create a threat, when the coupling among the individual systems will be weak leading to disbalance of all system or vice versa when the system is strongly coupled lead by one predominant artificial intelligence and in such a case showing the groupthinking effect.
ORGANIZATIONAL AND PEDAGOGICAL ASPECTS OF FORMATION OF PROFESSIONAL AND GENERAL ETHICS

the article reveals the formation of professional and general ethics in future professionals; the need to maintain the mental health of students is emphasized; introduction of technologies for creative transformation and modernization of modern higher education of students; development of general ethics to form the basis of professional ethics. The essence of the technology of formation of competencies of general and professional ethics in future teachers is revealed.
SISTEM INFORMASI TATA NASKAH DINAS ELEKTRONIK DI INSTANSI KECAMATAN PANDAAN DAN PEMERINTAH DESA MENGGUNAKAN METODE WATERFALL

&lt;p&gt;&lt;strong&gt;Abstract : &lt;/strong&gt;&lt;em&gt;Official script management is written information as an official communication tool made by authorized officials in government agencies. In terms of making official manuscripts in Pandaan District, they still use manual processes so that the service process is slow. The existence of these problems the writer will implement good governance by creating an electronic service manuscript information system using the waterfall method implementation, with the hope of producing an organized system. The results of this research are in the form of an electronic official script management information system using the waterfall method with the hope of facilitating the work of the State Apparatus.&lt;/em&gt;&lt;/p&gt;
ANALYSIS ON EFL LEARNERS’ CAPABILITY IN MASTERING TOEFL TEST ON READING COMPREHENSION

This research aimed at knowing learners’ capability in mastering TOEFL test on reading comprehension part for EFL Learners. It was a descriptive quantitative research. It was conducted at the fourth semester students of EFL Learners as the sample of research. The class consisted of 3 classes and the sampling used of this research was cluster random sampling by lottery the class. The sample was class A consisted of 25 EFL Learners. In collecting the data, the instrument was given in the form of reading comprehension of TOEFL test and it was consisted of 50 items dealing with mastering main idea, mastering explicit implicit information, mastering reference, mastering meaning of word, and mastering inferences. After collecting the data, it was analyzed descriptive statistics by operating SPSS 26 for windows to know the mean score of students’ test. The mean score of the test was 32.3. It was categorized into very low. Therefore, the students of EFL Learners had very low capability in answering TOEFL reading comprehension section. Therefore, it is significantly for the students who have low ability in reading comprehension to mastering the strategies in answering the reading test.
mammography classification model trained from image labels only

The Cancer Registry of Norway organises a population-based breast cancer screening program, where 250 000 women participate each year. The interpretation of the screening mammograms is a manual process, but deep neural networks are showing potential in mammographic screening. Most methods focus on methods trained from pixel-level annotations, but these require expertise and are time-consuming to produce. Through the screenings, image level annotations are however readily available. In this work we present a few models trained from image level annotations from the Norwegian dataset: a holistic model, an attention model and an ensemble model. We compared their performance with that of pretrained models based on pixel-level annotations, trained on international datasets. From this we found that models trained on our local data with image-level annotation gave considerably better performance than the pretrained models from external data, although based on pixel-level annotations.
Saúde mental de enfermeiros atuantes na pandemia de COVID-19

Introduction: The COVID-19 pandemic has brought new challenges for health workers. The numerous concerns, especially with contamination, generate psychological impacts as direct consequences. Objective: Explore and study the new reality of nurses and its impact on their mental health during the pandemic. Methodology: This is an integrative literature review carried out from June to July 2021, using the descriptors “Mental health”, “Coronavirus”, “Nurses” and “Pandemic”. A total of 182 articles were found, resulting in a final sample of 8 studies after applying all the inclusion and exclusion criteria, using the recommendations of the PRISMA method. Results: The 8 selected studies originated from 6 different countries, with 7 articles in English and 1 in Portuguese. The distribution among the databases consists of: PubMed (3), MEDLINE (3), Science Direct (1) and LILACS (1). Regarding the level of evidence, 4 studies presented level V and 3 articles presented level IV. Conclusion: The presence of stressors in the work environment of health professionals is recognized, in addition to work overload.
Education of pedagogical professionalism for students to satisfy the demands of innovation and improve the quality of teaching in Vietnam

The objective of the research: (1) Assessing the process of students’ forming pedagogical professionalism at Hanoi National University of Education (HNUE), Vietnam; (2) find effective solutions aiming at improving the quality of pedagogical professionalism education for students of this University, to meet the requirements of social innovation as well as upgrade the standards in teacher training. Research Methodology: We surveyed to collect information on the current status of pedagogical professionalism education for students of the Faculty of Psychology and Pedagogy in HNUE, Vietnam. Students: 95 male students, 108 female students and 18 lecturers in the Faculty of Psychology and Pedagogy in HNUE. Research results: Solutions proposed by the research team for implementation at HNUE.
Intelligent Offline Multi Object Recognition Walking Stick for The Blind

Vision is one of the most important characteristics of a human that aid their day to day activities. Loss of vision however affects the ability of humans to freely navigate their environment and recognized objects along their path. Existing object recognition systems for the blind are mostly cloud based and its performance depends on reliable internet access. This makes them unsuitable in places with unreliable internet. Therefore, in this paper, a multi-object recognition intelligent walking stick for the blind that is completely independent of the internet was developed. The system is divided into three units, detection, recognition and communication units. The detection unit make use of an ultrasonic sensor and a buzzer, for informing the user of an impending obstacle. The recognition system makes use of a camera for capturing images with Convolutionary Neural Network architecture and Mobile Network Single Shot Multi-Box Detector (MobileNet SSD) for detecting objects in images. The communication unit transmits the recognised objects through voice to the user in English Language. The entire system was deployed in a Raspberry Pi microcontroller due to its processing power. The result obtained from testing of the device on the field showed that the recognition unit achieved an average sensitivity, specificity, precision and accuracy of 87.26%, 67.45%, 89.07%, 82.50% respectively. This shows that the system is reliable and can be used in recognizing objects for the blind.
Analysis of Generative Deep Learning Models and Features of Their Implementation on the Example of WGAN

The paper presents architecture features, the learning process, and the scope of generative deep learning models. The main tasks of such models include data generation (images, music, texts, videos), transferring styles from one data to another, improving data quality, data clustering, anomaly detection, etc. It is noted that the results of generative models are commonly used for entertainment purposes. In addition, they can be used as data for learning other machine learning models, sources of new ideas for creative professions, tools for anonymization of sensitive data, etc. The article analyzes the advantages and disadvantages of basic generative models like autoencoders, variational autoencoders, generative adversarial networks (GAN), Wasserstein GAN (WGAN), StyleGAN, StyleGAN2, and BigGAN. The paper also describes a step-by-step study of the generative model implementation on the example of WGAN, which includes the basic architecture implementation and more complex elements. Examples of such elements are the introduction of conditional generation to add the ability to select the desired class and the algorithm of bilinear sampling to solve the problem of the so-called ‘checkerboard effect’. The final model, created as a result of the study and named CWGAN-GP_128, is capable of generating realistic images of dandelions and marigolds at a resolution of 128x128 pixels. The model learned on the authors' data set consists of 900 photos (450 for each class). The learning process includes affine transformations such as rotations and inversions to augment the images. It is emphasized that although the results of generative models are often easy to evaluate visually, along with the rapid progress of GAN, the problem of automating the process of checking the quality of generated data is growing. The final model is open for public access, and the results are accessible on the authors' website thisflowerdoesnotexist.herokuapp.com.
Content-Based Image Retrieval with Feature Extraction and Rotation Invariance

Over recent years, Convolutional Neural Networks (CNN) has improved performance on practically every image-based task, including Content-Based Image Retrieval (CBIR).Nevertheless, since features of CNN have altered orientation, training a CBIR system to detect and correct the angle is complex.While it is possible to construct rotation-invariant features by hand, retrieval accuracy will be low because hand engineering only creates low-level features, while deep learning methods build high-level and low-level features simultaneously.This paper presents a novel approach that combines a deep learning orientation angle detection model with the CBIR feature extraction model to correct the rotation angle of any image.This offers a unique construction of a rotation-invariant CBIR system that handles the CNN features that are not rotation invariant.This research also proposes a further study on how a rotation-invariant deep CBIR can recover images from the dataset in real-time.The final results of this system show significant improvement as compared to a default CNN feature extraction model without the OAD.
PROGRAM FOR INTERNATIONAL STUDENT ASSESSMENT (PISA) ANALYSIS OF ASIAN COUNTRIES USING K-MEAN CLUSTERING ALGORITHMS

The Organization for Economic Co-operation and Development (OECD) report shows that there are still some Asian countries at the lowest level in terms of achieving the Program for International Student Assessment (PISA) such as the Philippines, Lebanon, Indonesia, Kazakhstan, Azerbaijan, and Saudi Arabia. Based on these problems, it is necessary to group countries in Asia based on PISA indicators so that the characteristics of each country can be known through the k-mean clustering algorithm method. The data in this study are secondary data from the 2018 PISA results which include variables in reading, mathematics, and science. The sample in this study were Asian countries that participated in PISA in 2018 totaling 17 countries. Based on the results of clustering, there are 3 clusters formed, namely, cluster 1 is China and Singapore, which are countries with PISA capabilities above average. Cluster 2 is a cluster consisting of Malaysia, Brunei Darussalam, Qatar, Saudi Arabia, Thailand, Azerbaijan, Kazakhstan, Indonesia, Lebanon, and the Philippines with below-average PISA acquisition. Whereas in cluster 3 it is a cluster consisting of countries with medium capabilities in PISA acquisition such as Macau, Hong Kong, Korea, Japan, and China-Taipei.
Library Management System (LMS) Using JAVA

Abstract: A Library Management System is a system that is used to maintain the records of the library. It contains work like the number of the available books, the number of books issued, the number of books to return or renew. It helps to maintain a database that is useful to enter new books and records of books borrowed by the members with the respective submission dates. It will reduce the manual work done by the librarian to maintain the record of the library. It allows maintaining the resources in a more operative manner that will help to save the time. It is also convenient for the librarian to manage the process of books allocation. It is useful for students as well as a librarian to keep the constant track of the availability of all books in a library. Keywords: Library, Java, Management, System
Factors Determining the Minds of Juvenile Based on Improved Reading Habits

The habit of reading is a significant phase for creating a society of literate in this world. It natures an individual’s personality and it helps them to find creating new ideas and the proper method for thinking. At current situation, people cannot find much interest in reading books, magazines and journals etc., due to the domination of the media. As a result, there is the pressing need to develop the habit of reading among the people in the society. In this paper, the author has discussed the factors determining the minds of juvenile based on improved reading habits.