Reviewerly/exHarmony huggingface dataset:
KNOWLEDGE DISCOVERY DATABASES (KDD) PROCESS IN DATA MINING

Data Mining is a powerful tool for companies to extract the most important information from their data warehouse. These tools allow you to predict future trends and behaviors in order to be able to provide activities based on specific knowledge. Volume of information is increasing every day that we can handle from business transactions, scientific data, sensor data, Pictures, videos, etc. So, we need a system that will be capable of extracting essence of information available and that can automatically generate report, views or summary of data for better decision-making.Data mining is used in business to make better managerial decisions by:Automatic summarization of data,Extracting essence of information stored,Discovering patterns in raw data.Data Mining also known as Knowledge Discovery in Databases, refers to the nontrivial extraction of implicit, previously unknown and potentially useful information from data stored in databases.Keywords: Data Minig, tools, databases, data warehouse, knowledge.
Interactive teaching methods for primery school: the algorithm for designing interactive activities.

The article describes the results of the development and testing of an algorithm for designing interactive activities for primary school. The algorithm is developed taking into account the characteristics of modern primary school students, examining different interpretations of the concept «interactive» in different spheres of human life and fields of study (such as linguistics, sociology, psychology, pedagogy) and considering the problem of using the term «interactive» in the modern education system. The algorithm for designing interactive activities includes six sequential steps: to select the content; to choose a type of group for the activity; to create the activity in which each student will personally participate; to think over different options to provide choice for students; to select the technical means; to set a time limit. Each action of the algorithm is depicted from the perspective of a primary school teacher. The survey of the teachers found significant changes in teachers’ perceptions of the term «interactive», in their understanding of distinctive features of the interactive activities and difficulties to create suitable interactive activities. It is noted the importance of continuing research in the aspect of the influence of interactive activities on the educational achievements of primary school students (including the development of functional literacy). The article was prepared with the financial support of the Ministry of Education of the Russian Federation within the framework of the research project «The development of functional literacy among primary school students in the implementation of educational programs».
Enhanced Non Local Means Filter to Denoise MR Brain Images by Using Mean Absolute Deviation Error Measure

Now-a-days, Magnetic resonance (MR) images are using for diagnosing and treatment planning. Though, MR images are often contaminated by several kinds of noises such as Rician and Gaussian noises which are produced by the random thermal motion of electronic components. It diminishes the quality and trustworthiness of the images. This paper proposes an Enhanced Non Local Means Filter (ENLMF) to denoise Rician type of noise from MR images. Human brain is a complex structure that contains millions of neurons which makes acute changes in intensity of pixels. Therefore, the earlier model of NLMF might be improved to remove Rician noise from brain MR image. This study, implemented Dynamic window to enhance the noise removal process which utilizes Mean Absolute Deviation Error (MADE) to determine the window size. The method implemented in publically available noise introduced data set. The results also compared with the existing NLMF by visual and quantitative measures such as Peak Signal to Noise Ratio (PSNR) and Structured Similarity Index (SSIM) measure. The experimental results show that the proposed method provides 9% to 10% higher result than the existing NLMF.
Application of Water Conservancy Project Precise Management System in Reservoir

good work efficiency is inseparable from scientific, precise and standardized management. As an important management concept of modern management, precise management is used in all walks of life. We hope that through the standardization and refinement of the system, we can make the system management more efficient and accurate. Water conservancy project is used to control and allocate the surface water and groundwater in nature. It is built to resist flood and drought disasters, guarantee water resources supply, improve water environment and realize water conservancy economic purpose. Therefore, the application of information management in water conservancy projects, the construction of water conservancy project precision management system is conducive to achieve all-round, accurate management, and improve the comprehensive management level. This paper introduces the water conservancy project precision management system of the major modules and the use of methods.
human speech emotion recognition using machine learning

Abstract –The investigation of human discourse is a difficult examination territory as it concerns the discovery of user networks. Feelings assume an underlying part in human communication. The capacity to comprehend human feelings by breaking down voice is alluring in various uses of discourse acknowledgment in feelings can be found in various zones, for example, the association among PCs and people and call focuses. Already, feeling acknowledgment utilized straightforward classifiers on bag- of-words models. Nonetheless, the current work of feeling acknowledgment on Voice was done with the assistance of profound learning strategies on static voice information. The proposed strategy centers around expanding the general precision of feeling acknowledgment during calls utilizing man-made consciousness. The general point is to precisely perceive the different feelings that a specific speech communicates semantically.
LibGuides: Management of Engineering and Technology: Specialized Databases

This guide is for the NCU Management of Engineering and Technology specialization. It contains resources available in the NCU Library.
Towards Development and Verifications of Advanced Optimal Farm Machinery Route Algorithm

Efforts related to minimising the environmental burden caused by agricultural activities are key contemporary drivers in the precision agriculture domain.Controlled Traffic Farming (CTF) techniques are being applied against soil compaction creation, using on-line optimization of route planning for soil-sensitive field operations.The research presented in this paper aims at optimizing farm machinery routes to minimize the environmental burden.As such, it further advances existing CTF solutions by its complexity including (1) efficient field divisions, (2) U-turns in headlands, (3) obstacles in a farm machinery route and (4) terrain specifics.The developed algorithm is expressed as UML activity diagrams as well as pseudo-code.Results were visualized in 2D and 3D to demonstrate terrain impact.Verifications were conducted at a fully operational commercial farm (Rostěnice, the Czech Republic) against second-by-second sensor measurements of real farm machinery trajectories.The developed algorithm addresses two main viewpoints: economic (saved route, fuel and time) and environmental (among other, reductions of soil compactness and erosion, an increase of soil infiltration rate).
LibGuides: Interactive Exercises: Summon

H5Ps and other interactive learning objects related to library resources and information literacy
LibGuides: A Guide to Classical Music for Non-Musicians: Home

This guide was created as introduction to the basic materials of music and their use in the understanding and appreciation of different musical styles and periods.
Methods of Determination of Radiation Factors and Radioecological Conditions in Navoi Industrial Region

Radiation factors-exposure dose rate of gamma-radiation, specific effective activity (Aeff), specific activity of radionuclides, equivalent equilibrium activity of radon (EEA), activity of long-lived radionuclides (LLR), radon flux density (RFL), coefficients of radioactive equilibrium etc., and methods for definition of their significance in Navoi industrial region are actual tasks of radioecology. Values of radiation factors are regulated by normative international documents and documents of the Republic of Uzbekistan. The established norms of radiation safety are monitored in industrial and settlements as well as in the adjacent areas of the so-called observation points [1,7]. Exposure dose values are estimated by means of radiation analysis of soil, air, plants, drinking, waste and underground water in observation points of adjacent territories to sources of environmental contamination [2-6]. On the basis of the performed researches it is possible to determine -238U, 232Th, 226Ra, 40K concentrations in soil, water and technological products as well as to find the forms of elements in liquid phase using nuclear filters and to determine the fractional composition of uranium-containing solid fractions in gas emissions using nuclear filters. Based on the value of the enrichment factor of chemical elements in the soil, we can find a pattern of localization of man-made chemical elements in some areas of the studied areas of uranium production. On the basis of the studies conducted to determine the migration of chemical elements in the groundwater we can predict the possible values of groundwater contamination in the area of uranium and gold mining plants.The main component of the values of environmental exposure doses are radioactive pollutants and their compound in the soil, air, plants, drinking, waste and groundwater [8-18].
Deterring Algorithmic Manipulation

Does the existing anti-manipulation framework effectively deter algorithmic manipulation? With the dual increase of algorithmic trading and the occurrence of “mini-flash crashes” in the market linked to manipulation, this question has become more pressing in recent years. In the past thirty years, the financial markets have undergone a sea change as technological advancements and innovations have fundamentally altered the structure and operation of the markets. Key to this change is the introduction and dominance of trading algorithms. Whereas initial algorithmic trading relied on preset electronic instructions to execute trading strategies, new technology is introducing artificially intelligent (“AI”) trading algorithms that learn dynamically from data and respond intuitively to market changes. These technological developments have exposed significant shortcomings in the effectiveness of anti-manipulation laws, particularly regarding one of their fundamental goals: deterring market manipulation. Preventing manipulation remains a key feature of the legal regime governing the financial markets. Rampant manipulation undermines the viability of the market and, in the case of algorithmic manipulation, increases systemic risks within the market. Deterring algorithmic manipulation is thus essential to the viability and stability of the market. However, credible and effective deterrence of wrongdoing requires certainty of punishment, which is increasingly unattainable with respect to algorithmic manipulation under the existing legal regime. Specifically, the law of manipulation tethers liability to scienter, which algorithms cannot legally form. Further, deciphering the intent of the human behind the algorithm can be a near-impossible task in all but the most egregious cases. The scienter-focused nature of the anti-manipulation framework therefore diminishes the disciplinary power of the law, weakening deterrence and incentivizing algorithmic manipulation.This Article demonstrates that the scienter-centric analysis undergirding anti-manipulation laws creates gaps in the detection and punishment of algorithmic manipulation that weaken the current legal regime’s deterrent effect. The acute failure of the law to punish algorithmic manipulation incentivizes potential wrongdoers to utilize algorithms to cloak their misdeeds, exposing the markets to significant systemic harm. Notably, unlike other scholars and policymakers that view transparency as the ultimate solution to increase accountability for algorithms, this Article highlights the potential limitations of relying primarily on transparency. Rather, the Article urges changes to the legal framework to modernize its applicability: eschew the scienter requirement and, instead, focus on the resulting harm of the algorithm on the market. Together, these proposals are likely to credibly deter algorithmic manipulation, safeguarding the viability, efficiency, and stability of the markets.
EUCENTRE and seismic emergency: technical preparedness activities and response after the central Italy earthquake

The ASA (Advanced Seismic Assessment) module is a post-earthquake technical intervention service, developed over the years by the EUCENTRE Foundation through a series of national and European pilot projects, field exercises, and direct experience, after the latest major seismic events that struck Italy since 2009. The system consists of a service managed at the headquarters in Pavia for the development of damage scenarios, and of a mobile unit for the on-site damage assessments. After the Central Italy earthquake, the Foundation has been involved for about eight months in several activities, including provision of technical support to the Italian Department of Civil Protection, joint reconnaissance with internationally acknowledged research institutes.
An Introduction to Machine Learning Games and Its Application for Kids in Fun Project

Industrial Revolution 4.0 is the right time to democratize artificial intelligence in the world. It can be started from education, the target is the level of elementary, middle and high school. But the general curriculum still around in natural science, social science and language science. The challenge is how to introduce artificial intelligence earlier to the student and how to combine its material with the curriculum. “Machine Learning for Kids” is a web-based application which kids can explore artificial intelligence, especially in machine learning field with a fun project. The application provided to create a new project like animal classification. Kids can add a new label, such as mammal, insect, amphibian, bird, fish and etc. They have to add the animal name as an example of training data into each label. After kids added the training data, they can create the machine learning model. The experiment showed the confidence of the machine learning model test with a member of example reached 100%, the label prediction of all example was accurate. While the confidence of machine learning model test with another member of example reached between 14-17%, the label prediction of all example was also accurate. We recommended “Machine Learning for Kids” is one of the best web-based application for kids to explorer machine learning easily.
Experience of digitalization of personal archive collections and their further use

The article deals with the specifics of the digitization of personal archival funds on the example the unique documentary collection of the Chairman of the Council of Ministers of the USSR A. N. Kosygin. The algorithm of creating a complete, systematic electronic version of the collection, as well as some methods of preparation for the historical and biographical exhibition, are shown.
An environmental approach in designing a safe professional and educational environment

The article discusses the theoretical issues of designing a safe professional and educational environment. The environmental approach is substantiated as a methodology for this process. The environmental conditions that provide the teacher with safety and security in the implementation of professional activities are indicated. An attempt was made to determine the ratio of the structural components of the vocational and educational environment and the environmental conditions that ensure its safety. The stages and levels of designing a safe professional and educational environment have been substantiated.
FACIAL RECOGNITION ONLINE EXAMINATION ALONG MACHINE LEARNING

The COVID19 situation has made online examination as the primary part in education throughout the world. There are different parameters of remote proctoring such as audio proctoring, video proctoring, image proctoring, monitoring screen of the end-user attempting the online exam. With the help of all these mechanisms, can securely conduct and Online Exam, that too under a controlled and cheat-free environment. In this Project, the tool used is Python to test out the scikit-learn library since it is the industry standard for scientific tasks like regression. The Jupyter Notebook allows most anyone to run this code by own, we need to have scikit-learn, NumPy, matplotlib, Seaborn, Itertools, and imblearn installed and the dataset are imported on machine for virtual environment.The objective used in the process is. Facial recognization – when we appears to exam hall, they have been scanned all the student’s face id. So they can easily identify and recognise the students facial fraudulent works.
Automatic Sentiment Analyser Based on Speech Recognition

Analysis of the Emotion of a person has been developed over the earlier period decades. The majority of the works in it spun over text emotion analysis with content analyzing strategies. Yet, audio emotion analysis opinion is in the beginning phase of the research network. Our work presents the study of various algorithms of sentiment analysis to identify Emotion by dissecting the acoustic highlights of an individual's voice. The direction of study on datasets and the strategies which are utilized to recognize feeling through voice and actualized the framework to distinguish the best structure for the errand fully expecting and conveying it in a future application.
An Automatic Vehicle Routing and Tracking Technique Based on Video and Image Processing Techniques

In this research work an advanced route tracking application is designed based on video and image camera stabilization technique. The initial input video can convert the images and contain noise as well as extreme distortions. Therefore the following elements can affect the route tracking as well as mis-information gathering. In this paper a multi-media tool based mute tracking application is introduced to obtain mad condition as well as route features. The initial images are filtered by using adaptive median filter to minimize the noise. After filtration road condition can easily identified and separate the target and background, moreover the boundary conditions helpful for extracting the neighborhood target images. The following process is working based on angle, derivative-path and curvature calculations. After this primary process, preview image can be obtained on the screen, according to this the driving speed can be controlling to front wheel rotations. The random pursuit matching algorithm controls the later information and realization. The experimental outcomes show that proposed application has been helpful for driver less vehicle tracking easily. This investigation had been verified on various references speeds and managed with 0.04 meters.
Effect of Normalisation for Gender Identification

This work has considered standard data set for gender identification using machine learning approach. Various approaches are considered to achieve greater accuracy and low error (specificity/MCC). Number of experiments are done to learn optimal weights for different value of K = 5, 10, 15 and 20. From range of experiment, it is clear that higher K fold validation is giving better accuracy all time. When different K folds cross-validation is used, different techniques and different normalisation models are performing in different way. When K = 5 and 15, without normalisation and forward normalisation are performing best, and for K = 10, forward normalisation, and for K = 20 standard normalisation is working best.
Physics-guided Machine Learning for Scientific Knowledge Discovery

Machine learning (ML) has found immense success in commercial applications such as computer vision and natural language processing. Given the success of ML in commercial domains, there is an increasing interest in using ML models for advancing scientific discovery. However, direct application of ``black-box ML models has met with limited success in scientific domains given that the data available for many scientific problems is far smaller than what is needed to effectively train advanced ML models. Additional challenge arises due to the data non-stationarity in space and time. In the absence of adequate information about the physical mechanisms of real-world processes, ML approaches are prone to false discoveries of patterns which look deceptively good on training data but cannot generalize to unseen scenarios.
Best Computers For Serato DJ

Serato DJ is one of the most popular modern music production and DJing tools of this era, offering just more than enough specifications and support for ...
KEMAMPUAN MENGANALISIS BAHASA TIDAK BAKU DALAM TEKS BERITA SISWA KELAS VIII SEMESTER GENAP SMP UTAMA 3 BANDAR LAMPUNG TAHUN PELAJARAN 2018/2019

The problem in this study is related to the ability to analyze non-standard languages ​​in news texts. The aim of the study was to determine and describe the ability of eighth grade students in the second semester of Junior High School 3 Bandar Lampung 2018/2019 in analyzing non-standard language in the news text, the ability to improve, and knowing the factors that caused student weaknesses. The research method uses quantitative. The population of this study was the eighth grade students of the even semester of the Middle School 3 Bandar Lampung 2018/2019 academic year, totaling 50 students. The study sample was assigned 1 class, namely class VIII.2 with a total of 27 students. Taking it by cluster random sampling. Data collection uses performance reading news texts and analyzing and improving non-standard languages ​​in the text. The results showed that the ability to analyze non-standard languages ​​in the news text of grade VIII students in the even semester of the Junior High School 3 in Bandar Lampung in the 2018/2019 academic year was in sufficient category. The value achieved is 65 in the score range of 56-75. Of the 27 students, 22 of them were in the sufficient ability category with a cumulative frequency of 81%, while 5 students were in the less category or 19%. In the aspect of accuracy of analysis, the average score of students reaches 78 or is in the range of values ​​76-85 in the good category. In the aspect of the accuracy of arguments or improving non-standard languages ​​the average value is 53 or in the less category. Factors that influence students' weaknesses in analyzing and improving non-standard languages ​​in the news text include weak knowledge, lack of reading standard Indonesian language dictionaries, lack of practice analyzing raw and non-standard languages ​​in a text, and lack of asking teachers at school.
All guides: Using Videos in Canvas: ClickView

This guide provides instructions on linking and embedding Library videos, including playlists and clips, in your Canvas course and Reading List.
Data Sonification: Sounds from Around the Milky Way

A new project using sonification turns astronomical images from Chandra and other telescopes into sound.
Getting Familiar with WidgetKit in a Flash

This chapter will quickly introduce you to WidgetKit, Apple’s framework to develop beautiful and handy widgets for iOS homescreen and macOS Notification Center.
LibGuides: HIST2 - Primary Source Research Guide: Government Reform Resources

This guide provides resources and suggestions for locating both primary source materials and secondary sources that provide context for understanding those primary sources.