Reviewerly/exHarmony huggingface dataset:
Comparison of Several Machine Learning Algorithms in the Diagnosis of Cervical Cancer

Cervical cancer is a major disease endangering the health of women around the world. Every year, a large number of people die because of it. It also causes a huge economic burden to the families of patients. The application of machine learning algorithm in the diagnosis of cervical cancer can reduce the cost of manpower and material resources and achieve better diagnostic results. This paper aims to find a classification model with higher accuracy and better effect to classify cervical cancer patients. In this paper, the survey data for cervical cancer provided by UCI database are used, and the combination of up-sampling and down-sampling is used to balance the data set. Then, the data are predicted through SVM, KNN and CART respectively. After repeated experiments, we found that the prediction effect of CART algorithm has been significantly improved with BOOSTING. The model performed well in the identification of cervical cancer patients. All cervical cancer patients in the data were correctly classified, and the overall accuracy was 98.76%.
Decentralized Application for the Classification of Products Based on IPFS and Blockchain

This paper describes the construction of a prototype web platform to classify and recommend products, in an unstructured format, specifically using images. The platform uses information taken from the image repository that communicates with it. Using technologies such as Blockchain and the Interplanetary File System (IPFS), it provides a new approach that offers users the benefits of these technologies to protect the quality of stored information and content access.
Prediction of Rainfall Characteristics Based on Fuzzy Expert System

Rainfall prediction is one of the most extremely important and trickiest job in the modern world because, Rain is the lifeblood of human survival, of life on our planet. Gorgeous beauty of fuzzy logic was described by various author for prediction in various field. In this work, fuzzy logic is applied in proposing a model to predict rainfall percentage with parameters. Fuzzy Expert System inputs(parameter) include the temperature, humidity, wind speed , Dew point etc., with Output as rainfall Percentage .Here we develop a new model as RPFES Model to predict rainfall percentage for particular geographical location of Tamil Nadu. There are four steps for developing RPFES Model : The first step is Fuzzification process by triangular membership function for representing the input variables and output variables. The next step is Fuzzy Inference with Fuzzy Rules the method applied in this research work are Root Sum Square (RSS). The Root Sum Square of drawing inference was employed to infer the data from the fuzzy rules developed and finally we move to Defuzzification process for getting Rainfall percentage by individually. From RPFES Model, Individual Person get the Rainfall Prediction as Percentage with purely by Fuzzy Logic and not by Metrological Center. Weather Prediction is the major essential and challenging operational responsibilities which are carried out by meteorological services all over the world.
diman: A Clojure Package for Dimensional Analysis

diman (dimensional analysis) is a Clojure based scientific software package with the ability to: create dimensional formulas, create dimensional equations, check dimensional homogeneity (consistency), and derive dimensionless products.diman provides functions for each step of the analytic process for checking dimensional homogeneity or deriving dimensionless products; the repetitive operations (computational) are hidden.Users can write compound functions that perform a desired process.Thus, not only is the computational labor saved, but also introspection of the analysis is possible; the analyst is able to go through the steps of dimensional analysis.
Remote Intelligent Guidance System Based on Augmented Reality

The special environment of the Space Station and complexity of space equipment require more efficient and accurate on-orbit maintenance methods. Space equipment failures can be solved by adding maintenance plans in the way of induced maintenance. However, the induced maintenance plan cannot be added unlimitedly, time expenditure and cost consumption should be considered. Using remote communication with experts on the ground can effectively save costs and improve maintenance efficiency. Under current conditions, astronauts cannot connect experts through conventional communication methods. To sum up the foregoing, designed remote intelligent guided maintenance system based on Augmented Reality, which is applied to the actual work field where remote experts guide astronauts to coordinate maintenance. Compare and choose the right software, hardware, and development platform. Realize remote data processing and transmission, world-earth simulation communication, remote virtual information addition, and information storage. The astronaut terminal and the remote expert terminal realize audio and video data transmission based on socket multi-threaded communication, which breaks through the limitations of astronaut’s local operation. Develop and test the system on Unity platform, software runs stably, and the remote auxiliary maintenance tools are intuitive and convenient, which can effectively realize the remote collaboration between ground and the Space Station.
Relationship Between Metals In Ovacık Stream Sediment Samples

Ovacık Village is located in Balıkesir province and is 12 km away from Balıkesir Center. The GPS coordinates of Ovacık Village are 39° 43' 51'' North and 27° 47' 37'' East. The stream sediments in the study area consisted of the erosion of magmatic, metamorphic and volcanic rocks and surface waters and eroded rock particles along the stream bed. The relationship between metals in stream sediments has been investigated on the basis of geochemical properties. As, Cd, Cu, Mn, Ni, Pb and Zn element contents of 23 stream sediment samples were taken from different locations from Ovacık village and its surroundings. The minimum, maximum, medyan, median and standard deviation values of these metals in the stream sediments were calculated and it was observed that the mean values were higher than the standard deviation values. The minimum and maximum values (ppm) of the metals studied As: 7.7 - 51.3, Cd: 0.13 - 0.58, Cu: 25.2 - 70.6, Mn: 661 - 1135, Ni: 8.6 - 33.7, Pb: 12.3 - 57.7 and Zn: 59 - 220 According to the Spearman correlation coefficient values, a strong positive correlation was observed between As - Cu, Cd - Pb, Cd - Zn, Cu - Ni and Pb - Zn metal associations (p &amp;lt;0.01). Factor analysis was made with the obtained analysis results and 3 different factor values were created and analyzed. Factor 1: Cd - Pb - Zn association and 37.01% of the total variance; Factor 2: Cu - Mn - Ni association and 24.7% of the total variance; Factor 3: As and total variance was 18.4%, the total variance value was found to be 80.1%. The spatial distributions of the metals were analyzed using the Surfer 9.0 program in the creation of the distribution maps. As and Cu elements at locations 16 and 17; Mn and Ni elements at locations 3, 6 and 7; Cd, Pb and Zn elements have the highest values in locations 3, 12 and 20, they show a similar distribution.
Perancangan Sistem Identifikasi Tipe Sidik Jari Manusia Menggunakan Matlab

Human fingerprints are unique in this world.This is why human fingerprints are frequently used as a form of identification or self-recognition.Human fingerprints are classified into three categories: whorl, arch, and loop.The wavelet transformation is used because it is capable of identifying discontinuous lines.Because human fingerprints contain discontinuous lines, this method is ideal for recognizing fingerprint images, which are then compared to database images.Additionally, the method of image processing with Matlab software and integration with a GUI (Graphical User Interface) is described, so that it can be used to recognize human fingerprint types.
Application of Video Conference Media in Learning

The problem in learning is the inaccuracy of educators or lecturers in using learning media, in fact some lecturers do not use learning media. Whereas the learning media is everything related to tools and facilities with the aim of conveying information or messages in a lesson and streamlining communication between educators and students. Video conferencing is a medium that can display moving images with the help of signals. The purpose of this study was to look into how video conferencing was used to assess student achievement. This research was conducted on students of the accounting training study program at the University of Palembang in the management accounting course. The descriptive analysis was adopted in this study. Observation and testing are the methods used to collect data. The results showed the success of the learning process with the use of video conferencing tools. With the application of video conferencing media, it encourages students to be more enthusiastic about learning and observe carefully the material being taught so that it can improve student learning outcomes well.
Analysis and Design of Inpatient Daily Cense Information System in Bhayangkara Bengkulu Hospital

Background: Progressing technology in the world need to fast and accurate information in the hospital agencies as the basis for appropriate making decision. The inpatient daily census reporting of system Bhayangkara Hospital Bengkulu don't have utilized the Inpatient Daily census system electronically and still uses a manual system, so that the processing of report data is less than optimal. There are still a lot of inputting errors, inaccurate data, and inefficient time and energy. This study to aim design system information inpatient daily census reporting application at the Bhayangkara hospital to existing problems solving.Methods: The method used in designing and making this application is by utilizing software development methods, namely the waterfall method which includes identification, analysis, design or design, implementation and maintenance of the system.Results: The results this study is creation of an application to facilitys the processing of data into an inpatient daily census report that is needed and to overcome the problems that arise because of the report processing system manually. Design and Creation of Inpatient Daily Census Applications with Visual Basic 6.0 Programming at Bhayangkara Bengkulu Hospital have been made with the results of an analysis of existing systems and according to the method used, and the design of the forms that have been made in accordance with the manual form or home party needs sick and can simplify filling out forms and processing the data.Conclusions: At Bhayangkara Bengkulu Hospital still uses a manual inpatient daily census system, and not on time for reporting daily cencus patient data. The data structure contained in the ledger consists of patient identity, patient diagnosis, and others. There are three processes in the stage of analyzing the needs of the inpatient daily census system, namely the data input process, data processing and data output processes. ledger, patient data consisting of patient identity, doctor's name, patient diagnosis, treatment room, and treatment class. In designing the daily inpatient census system at Bhayangkara Bengkulu Hospit consists of patient data forms, incoming patients, outgoing patients, and patients moving. The implementation of the daily inpatient census system at the Bhayangkara Bengkulu Hospital has carried out socialization and discussions about the user interface design to officers or users of the electronic daily census system. And the maintenance of the daily inpatient census system is carried out in several stages (1) corrective, by correcting design and errors in the program, (2) adaptive, by modifying the system according to user needs, (3) perfective, namely processing census data computerized.
A Psychoanalysis of Data Privacy Maintenance Issues in Social Network using Data mining

The existing data sharing systems relates with the on-line social networks (OSNs) suggest encoding of information before sharing, the multiparty get to the executives of scrambled information has turned into a troublesome issue. A safe information sharing subject proposed in OSNs upheld figure content approach trait based and Elliptic Curve Cryptography algorithmic principle re-encryption and mystery sharing. The work relates the gatekeeper clients' delicate information grants clients to redo get to approaches of their information thus source scrambled information to the OSNs administration provider. The proposed technique displays a multiparty get to the executive’s model that enables the communicator to refresh the entrance strategy of figure content. The characteristics fulfill the common access strategy. The work needs a fractional mystery composing development inside which the calculation overhead of client is essentially diminished by strengthening the vast majority of the mystery composing activities to the OSNs administration provider. Moreover, the check capacity on the outcomes originated from the OSNs administration provider to guarantee the rightness of fractional decoded figure content. The present subject partner affordable properties disavowal philosophy that accomplishes each forward and in reverse mystery. The insurance and execution examination results demonstrate that the arranged subject is secure and efficient in OSNs.
ANN-Based Handwritten Digit Recognition and Equation Solver

It is well known that handwritten digits recognition may be a complicated job that is incorporated in a variety of applications. It is been largely employed by machine learning enthusiasts and researchers for developing apps like bank check processing. The most important task for the identification of a mathematical expression is to segregate the characters and then classify those characters. Due to their random nature, handwritten digits are not recognized by hard computing, and if recognized, the complexity is way too much. In this paper, an artificial neural network has been enforced and trained using a digits data set, to acknowledge and identify written digits from zero to nine and mathematical operators to unravel a mathematical equation.
Quantifying abstraction in neural networks to increase understanding of human brain processing

Training simple neural networks to form abstract representations valuable for neural systems, machine learning, artificial intelligence
Online Learning Policies and Indonesian Language Learning Constraints during the Covid-19 Pandemic

This research aims to analyze online learning policies and the problems of obstacles of teachers, learners, and parents in learning Indonesian in the covid-19 pandemic. This type of research is a case study at Muhammadiyah 4 Yogyakarta Junior High School and literature study using secondary data collected through books, journals, websites, and other sources related to research problems. Data collection uses interview techniques and document analysis. Data analysis uses qualitative descriptive techniques, consisting of data collection and subtraction, data presentation, and conclusion withdrawal. The results showed that the distance learning policy implemented at Muhammadiyah Junior High School 4 Yogyakarya was in accordance with the Circular Letter (SE) of the Ministry of Education No. 4 of 2020 on the Implementation of Education Policy in the Emergency Period of The Spread of Coronavirus Disease (COVID-19). The policies implemented include policies to provide student learning experiences, provide life skills education, learning in accordance with student conditions, the process of awarding assessments, and the process of Admission of New Learners (PPDB) and School Operational Assistance (BOS). On the other hand, there are also learning obstacles for teachers, learners, and parents in Indonesian learning experienced during the diverse covid-19 pandemic. Teacher constraints are on aspects of the use of learning applications, weak internet network access, unpreparedness with online learning media, learning materials that cannot be applied optimally, and research to learners. Student constraints are on aspects of inadequate learning facilities, weak internet access, inactivity in following learning, psychological conditions of stress and boredom, many tasks, and difficulties in operating learning applications. Parental constraints are on socio-economic aspects and supervision or mentoring of children in online learning at home.
THE ROLE OF THE TEACHER IN THE FORMATION OF THE PEDAGOGICAL COMPETENCIES OF THE PARENTS OF PRIMARY SCHOOLCHILDREN Sabina Guliyeva

The article emphasizes that reforms are being implemented in the field of education in our country today.New educational infrastructures are being created, content is being updated, and new approaches are being applied to the training of teachers.However, these are not enough to succeed in education, because the views of the majority of parents on the education of children do not meet modern requirements.Family-school relationships weaken year after year as students move into the upper grades.The pedagogical skills of parents lag behind the requirements of educational reform.The article examines the impact of family-school cooperation on the formation of pedagogical competencies in parents, analyzes various models of pedagogical skills development in parents, traditional and non-traditional forms of parent-teacher cooperation.
Research on Position and Posture Estimation of Rotated Workpiece Based on Image Recognition

In order to improve production efficiency, industrial robots are gradually applied to the manufacturing industry. It is necessary for industrial robots to obtain the position information and posture information of workpieces placed randomly to complete the tasks such as grasping, sorting and assembling. However, the algorithms based on traditional machine vision are sensitive to a series of factors such as illumination intensity and workpiece surface smoothness, which makes it poorly adaptable. To enhance the robustness and accuracy of robot operation, a position and posture estimation algorithm of the rotated workpiece based on image recognition is proposed. The proposed algorithm adopts the TextBoxes&#x002B;&#x002B; algorithm to predict the four vertices of the workpiece. The position information and posture information could be transformed from the smallest rotated rectangle containing the four vertices. The proposed algorithm has been evaluated on the custom dataset including six kinds of workpieces. The experimental results show that the proposed method can control the average position error and the peak position error within 0.11 mm and 0.5 mm, while the average posture error and the maximum posture error are no more than 0.40&#x00B0; and 2.92&#x00B0;, respectively. The proposed method could detect workpieces of uncertain positions and different postures, which is beneficial for the robots to adapt to the external environment automatically.
Information technologies of teaching in a secondary school

The conference participants are offered components of the educational and methodological complex in physics, which are obtained not by advanced pedagogical experience, ie by trial and error, but by detailed and complete analysis and calculation of structures and algorithms of the educational process in secondary school and its individual components. It is a guide for students, systematization of educational information, algorithm for solving physical problems, solving standard physical problems on a computer, diagnosing student performance and rating assessment of knowledge.
Communication Patterns Used During Learning From Home Mentoring At Kindergarten

Examining the involvement of parents in finding communication patterns has become very relevant due to the importance of Learning From Home activities.Therefore, this research aims to describe the communication patterns used by teachers and parents in assisting children as well as the aspects that influence the successful implementation of Learning From Home mentoring.This descriptive quantitative research used a population consisting of 6 teachers and 121 parents from the Kramat Jati State Kindergarten, East Jakarta, Indonesia, and employed questionnaires for the data collection.Subsequently, the results revealed several communication patterns between teachers and parents during Learning From Home activities, namely cooperative, interpersonal, transactional, and collaborative.Various influential aspects in successfully implementing this learning process include planning with parents, parental mentoring and guidance, facilities for customer complaints through a Whatsapp group, and motivational aspects provided by parents based on directives from teachers or the school.
Image Adjustment for Multi-Exposure Images Based on Convolutional Neural Networks

In this paper, we propose an image adjustment method for multi-exposure images based on convolutional neural networks (CNNs). We call image regions without information due to saturation and object moving in multi-exposure images lacking areas in this paper. Lacking areas cause the ghosting artifact in fused images from sets of multi-exposure images by conventional fusion methods, which tackle the artifact. To avoid this problem, the proposed method estimates the information of lacking areas via adaptive inpainting. The proposed CNN consists of three networks, warp and refinement, detection, and inpainting networks. The second and third networks detect lacking areas and estimate their pixel values, respectively. In the experiments, it is observed that a simple fusion method with the proposed method outperforms state-of-the-art fusion methods in the peak signal-to-noise ratio. Moreover, the proposed method is applied for various fusion methods as pre-processing, and results show obviously reducing artifacts.
A case study in authorship attribution: The Mondrigo1

In this paper, we present authorship attribution methods applied to ¡El Mondrigo! (1968), a controversial text supposedly created by order of the Mexican Government to defame a student strike. Up to now, although the authorship of the book has been attributed to several journalists and writers, it could not be demonstrated and remains an open problem. The work aims at establishing which one of the most commonly attributed writers is the real author. To do that, we implement methods based on stylometric features using textual distance, supervised, and unsupervised learning. The distance-based methods implemented in this work are Kilgarriff and Delta of Burrows, an SVM algorithm is used as the supervised method, and the k-means algorithm as the unsupervised algorithm. The applied methods were consistent by pointing out a single author as the most likely one.