Reviewerly/exHarmony huggingface dataset:
Anomaly Detection in Videos Using Deep Lnnearning Techniques

People’s safety in a public place is very important and this can be attained with the help of anomaly detection. This paper presents an approach to automatically detect abnormal activities in crowded scene. In light of this, we are developing a model in deep learning algorithms namely CNN and VGG16. We are collecting the anomaly and normal CCTV videos to build this project. Then we train with those videos with our algorithms to achieve best precision.
Implementasi Aplikasi Manajemen Mess (AMM) Berbasis Web

The guesthouse management process of PT PPA is done conventionally, the Group Leader (GL) and the admin coordinate face to face for data collection or changes in employee data on the homestead dwellers. Temporary data collection is done by paper, then entered by MS. Excel. Reporting on homesteads is done by MS. Excel. If there is a change in data, then the reporting of the guest house is invalid. The researcher's goal is to implement a guesthouse management application to accommodate real-time data collection by the Group Leader. Reporting on the residents of the guesthouse can be done based on the date of the guesthouse management transaction. Testing is done by black-box testing and user acceptance test (UAT). All test results are functionally successful, and the test is carried out by the IT department. Based on the UAT test, the mes management application has an attractive appearance, is very easy to use, is very helpful for room relocation, is very in accordance with the proposed design, is very well organized by employees' rooms, is very suitable for the data entered and passwords can be hidden very well.&#x0D; &#x0D; Index Terms—guesthouse; homesteads; management; reporting; User Acceptance Test (UAT)
New Approach for Detecting Spammers on Twitter using Machine Learning Framework

Social network sites involve billions of users around the world wide. User interactions with these social sites, like twitter have a tremendous and occasionally undesirable impact implications for daily life. The major social networking sites have become a target platform for spammers to disperse a large amount of irrelevant and harmful information. Twitter, it has become one of the most extravagant platforms of all time and, most popular microblogging services which is generally used to share unreasonable amount of spam. Fake users send unwanted tweets to users to promote services or websites that do not only affect legitimate users, but also interrupt resource consumption. Furthermore, the possibility of expanding invalid information to users through false identities has increased, resulting in malicious content. Recently, the detection of spammers and the identification of fake users and fake tweets on Twitter has become an important area of research in online social networks (OSN). In this Paper, proposed the techniques used to detect spammers on Twitter. In addition, a taxonomy of Twitter spam detection approaches is presented which classifies techniques based on their ability to detect false content, URL-based, spam on trending issues. Twelve to Nineteen different features, including six recently defined functions and two redefined functions, identified to learn two machine supervised learning classifiers, in a real time data set that distinguish users and spammers.
The Effect of BTCLS Training on Emergency Knowledge of Dharma Husada Nursing Academy Kediri Graduates

Basic Trauma Cardiac Live Support (BTCLS) training for nurses is an effort to improve skills to overcome emergency events that occur outside the hospital due to accidents / trauma or in the hospital due to diseases that impact cardiac arrest. Training is an activity to increase skills, knowledge and skills for nurses in providing appropriate and prompt care to patients. The purpose of the research was to find out the effect of BTCLS training on emergency management knowledge for akper dharma husada kediri nursing alumni. Research design with pre-experimental method with one group pre-post test design approach. . Research samples  50 people with simple random sampling techniques. Data collection used questionnaires and data analysis using t-test. The results  obtained a calculated value of 23.25 and a significance value of 0.000. Concluded the influence of BTCLS training on the knowledge of emergency management for graduates.
Literature Learning: the Formation of Character Education through the Study of Poetry

Learning literature is one way to shape student character education. One of the fields of literature learning that can shape character education is the Poetry Study course. The 1945 Constitution of the Republic of Indonesia is in line with the basic objectives of education, namely to educate a nation that has faith, is cautious and has a noble character. In this case, good character education for students is very important. Character education through the Poetry Study course is implemented by semester II students of STKIP Muhammadiyah Bogor in the very good category. This study took data by distributing questionnaires and observations. The formation of character education in this study focuses on religious values ​​which consist of worship, trust, sincerity, morals, and honesty. As many as 30 students were given a questionnaire. The results of the questionnaire show the percentage values ​​as follows; worship 88%, mandate 91%, sincere 88%, morals 89%, and honest 88%, so the average percentage is 89% with a very good category. Direct observations were made and it could be concluded that the lecturers of the Poetry Study course had indirectly shaped character education for students, because the Semester Lecture Plan contained the values ​​of character education in the material as well as in the learning process. Based on the results of questionnaires and observations, it can be concluded that the formation of character education for the second-semester students of STKIP Muhammadiyah Bogor is categorized as very good through literary learning in the Poetry Study course.
Geochemical Characterization of the Oil Source Rocks in the Ahwaz Oilfield, Southwestern Iran

The Ahwaz oilfield is located in the Dezful embayment of the Zagros fold-thrust belt in SW Iran. The oil source rocks predominantly with the argillaceous lithologies include the Kazhdumi, Gurpi, and Pabdeh formations as well as the basal part of the Asmari Formation. The concentrations of the major, trace, and rare earth elements (REEs) of these lithologies were determined using x-ray fluorescence spectroscopy (XRF) and inductively coupled plasma-emission/mass spectrometer (ICP-ES/MS), in order to infer the geochemical characteristics of the oil source rocks. The North American Shale Composite (NASC)-normalized major oxides displayed a positive anomaly in CaO, negative anomalies in other oxides and no anomaly in P2O5. According to the spider diagram of normalized trace element, there was enrichment in V, Ni, Cu, Cd, Pb, and Th values. In the NASC-normalized REEs pattern, the oil source rocks mostly display a smooth distribution shape, negative cerium anomaly, and slightly positive anomaly in the middle rare earth elements (MREES: Sm-Ho) values. The concentration of V, Ni, Co, and their ratios suggested a mixed marine and terrigenous source input. The ratios of redox-sensitive elements such as Ni/Co, V/Ni, V/V+Ni, Th/U, and Ce/Ce* suggested that the oil source rocks were mainly deposited under anoxic condition.
Holistic Decision-Making Frameworks: Accountability, Transparency, and Communication

Author(s): Dundon, Kate; Hughes, Margaret; Jones, Jasmine; Jones, Sarah R; Kim, Christine | Abstract: Panelists in this traditional session will discuss holistic decision-making frameworks for collection management activities. They will share how to build accountability to their organizational mission and values in these frameworks, as well as transparency in decision-making and strategic thinking to achieve long-term goals. In particular, the panelists will focus on how they are thinking about and embedding principles of diversity, equity, and inclusion in these decision-making frameworks. The panelists represent a variety of institutional perspectives with differing stakeholders, priorities, legacies, and processes in place, as well as a range of collection management functions, which includes prioritizing processing; strategic decision-making related to backlogs, reappraisal, and discovery; ethical and legal responsibilities towards contributors of metadata; and the creation of a DEI interest group to critically examine all areas of collection management.
Grau de pertencimento como insumo para classificação automática de textos: uma abordagem sintática

Grouping documents into categories is one of the solutions adopted to streamline the information retrieval process, which is increasingly relevant due to the large amount of information available today. The manual localization of documents of a specific theme, available in digital repositories, involves reading the title, abstract and keywords, in addition to further detailed evaluation in order to identify whether the publication belongs to the desired thematic axis. Considering the number of publications in a digital repository, manually locating all the desired texts on a given topic can be laborious and time-consuming. This research proposes an architecture for automatic classification of texts that is based on syntactic questions, that is, it undertakes a comparison of n-grams, which are combinations of n-pairs of words that are identified throughout the text. An exploratory applied research was carried out, which applied a type of supervised learning, fundamentally based on the document representation model called bag-of-words (BoW). The paper’s macro objective was to classify texts in general, according to pre-defined categories, by generating and comparing degrees of belonging between texts, as one of the key criteria. The results of these comparisons, using n-gram = 3, demonstrate that in the use of classifications by n-grams, the greater the number of grams, and with the removal of the stop words, we obtain a reduced degree of belonging, demonstrating greater rigor in identifying the match during the classification. In order to have greater confidence in the results, a larger training corpus is necessary to expand the number of words that characterize the pre-defined categories, to be used in the classification of the texts.
Machine Learning Algorithms Analysis On The Application Of Cancer Analysis

Over the last decades Machine Learning (ML) evolved from the end of the career of few computer enthusiasts, which exploited the possibility of computers being able to play games, to a computer discipline that did not just provide the basis for statistical computation principles of learning in a pro-computer environment. In addition, several algorithms have been developed which are regularly used for text interpretation, model recognition and many other commercial purposes and led to a separate research interest in data mining, which identify hidden regularity or irregularities that grow by the second in social information. Bosom most malignancies have turned out to be a standout amongst the most not bizarre sicknesses among women that outcome in biting the dust. Bosom most growths thinks about finished the previous decade has been wonderful. The pivotal changes and novel methodologies help in the early recognition, in putting the levels of the cure and in evaluating the response of the influenced individual to the cure. The reason for this paper progressed toward becoming at some phase in the writing evaluation of diaries and distributions inside the subject of records mining in PC innovative know-how and building. The examination focused on more present distributions in bosom malignancy.
Cyberbullying – A Critical Analysis of Laws, Criminal Responsibility and Jurisdiction

It is vital to look upon the data of Cyber Bullying cases and the age for which the accused is held responsible. Statistics reveals that criminal minded people who are on the borderline of the ‘age’ who could be charged under IPC for some blunt crimes are being treated liberally. Cyberbullying, also known as Internet bullying, is a form of criminal activity that falls under the broadcategory of cybercrime. Since there are different types of cyberbullying and abuse, it’s crucial to know what counts as “cyberbullying.” If we look at the dictionary meaning of a bully, we can see that it is described as “seek to hurt, threaten, or coerce - someone perceived as vulnerable”. Bullying is described as any individual or group of individuals who seeks to injure, coerce, intimidate, or threaten another.Such actions or action are most commonly seen on social media sites as well as in chat boxes and gaming websites. Cyberbullying occurs when an individual or group of people bullies or harasses another person using digital technology on the internet or in another digital sphere. This can include things like posting private photographs and videos without permission, creating fake accounts and spamming groups or individuals online, body shaming, making memes and videos of people, often celebrities, making mess ups or slips, and so on. According to a 2016 UNICEF survey, one in every three internet users worldwide is a child, while the latest ‘India Internet Report 2019’ indicates that two out of every 3internet users in India are between the ages of 12 and 29. As a result of their psychological nature, this community of internet users is often targeted by online bullies. The number of incidents of cyberbullying and abuse has increased as a result. Indian women and teenagers became the victim of Cyberbullying and cases increased by 36% in just one year.
Fuzzy Clustering Algorithm to Catching Pattern of Change in District/City Poverty Variables Before and The Beginning of The Covid-19 Pandemic in Sulawesi Island

The first goal of the SDGs is to end poverty in any form. The COVID-19 pandemic has greatly affected several economic indicators, especially absolute poverty, especially in Sulawesi Island, which has increased poverty indicators, leading to the movement of values between districts/cities. The grouping will show similar characteristics of absolute variable poverty. By the Fuzzy method clustering, each observation has a degree of membership so that from the degree of membership can be identified which areas have vulnerable to move from one cluster to another. Grouping using fuzzy algorithms will get an overview of districts of concern to the government during the pandemic so that the variable indicators of absolute poverty do not worsen due to the pandemic. Comparison with the absolute variables of poverty in 2019 and 2020 in the headcount index (P0), Poverty Gap Index (P1), and Poverty Severity Index (P2) in districts/cities on the island of Sulawesi based on silhouette coefficients shows that optimum clusters formed as many as 2 clusters, with a coefficient of 0.57 and 0.60 respectively. Cluster 1 has characteristics including areas with absolute poverty rates that tend to be more prosperous than cluster 2 in the 2019 and 2020 data groups on the island of Sulawesi. The fuzzy algorithm detects areas prone to displacement from cluster 1 to cluster 2, namely Bombana, Bone, Sangihe Islands, South Konawe, and Siau Tagulandang Biaro in 2019 and Bombana, Bone, Sangihe, and Maros Islands in 2020. The COVID-19 pandemic in March 2020 has not had much impact on the macro indicators of poverty seen in the transfer of membership from 2019 to 2020, which only occurred to 3 districts that changed, namely bolaang mongondouw and konawe selatan from cluster 1 to cluster 2 and Maros from cluster 2 to cluster 1.
Academic article: Trends in model changes

The article aims to determine the changes in the model of the speech genre of the Russian academic article in the field of humanities over the past 120 years. Methodologically, the analysis is focused mainly on identifying cognitive (logical-structural), pragmalinguistic (identifying the leading speech strategies) and formal (the form, article sections, text volume) characteristics of articles. The research suggests that during the analyzed time period, divided into four parts (1900–1930, 1930–1960, 1960–1990, 1990–2020), this speech genre has acquired the features of a hypergenre due to the fact that the following mandatory elements were included into the model: an Abstract, Information about the author, and Keywords. According to the analysis, one can see a specific trajectory in the formation of a model of a Russian academic article genre, the strengthening of national ways of information presentation and addressing in contrast to the enhancement of formal indicators. The obtained data is confirmed by the analysis of the frequency of speech strategies implementation (analytical, characterizing, modeling, methodological, classifying, reviewing, problem stating, descriptive, informing) and the analysis of the peripheral speech genres included into the article – affiliation (gratitude, appreciation), evaluation (criticism, approval, reproach), reflexive (justification, reference to authority), and prognostic (forecast, recommendation, suggestion) ones. Fluctuation in their frequency reflects internal trends related to historical causes and changes in scientific paradigms. Thus, the results of the research on the academic article speech genre in the field of humanities indicate that the unification of the Russian and Western European (Scopus) models of this speech genre is not inevitable.
University Life Online

The 21st century university is highly technological and much of university life is lived online. To succeed at university, a student must be confident to operate online and be digitally literate. This means being able to understand, use, adapt to and innovate with technology. This chapter begins by exploring why digital literacy is important and how it is relevant to university life. Next, it examines what universities will expect of you in terms of digital life. The chapter then outlines the digital attitudes, attributes and skills you will need to develop, and how these relate to other skills and attributes, such as finding information online. By developing each of the elements that will be discussed in this chapter, you will be well equipped for online university life.
Real-Image Transformation into a Caricature Image Using Neural Network

Multimedia is an area which is evolving at a greater extent day by day and it forms a great are of interest in machine learning and artificial intelligence. The caricature of a real time image is defined as a cartoon style of the corresponding object. It can be widely used process in the area of computer graphics as performing the same process manually for each picture. And hence this paper proposes a method of converting a real-time image into its caricature. The proposed methodology uses a concept of fully connected network to convert the real time image into its cartoon style. The experiments show improvised results up to 90% when compared to the existing methods. The experiments also prove that our model has strong applicability for translating real time images.
Technical Analysis of the Station Equipment IOT Management System

Abstract Traditional BAS systems in subway stations have problems such as inflexible deployment, high implementation costs, weak edge computing capabilities, and low integration, which are not conducive to the realization of convenience and intelligence. In response to the problems of the traditional BAS system, Guangzhou Railway Institute designed and applied a brand-new station equipment IOT management system. This article first analyzes the overall technology of the new system. In addition, the article also shows the hardware and software and core applications of the new system. Finally, the article describes the characteristics and main benefits of the new system.
Case Study : D’Roi F&B Industries / Nurul Syahirah Hasbi

D’Roi F&B Industries is the manufacturer for instant paste and maker of “Bawang Goreng”. All the recipe for instant paste are created by the owner herself
An Analysis of Students’ Perception on Synchronous and Asynchronous Learning in Speaking Skill During Pandemic Covid-19

During the pandemic Covid-19, teaching and learning system has been changed to online learning mode, especially in teaching of English as a foreign language. This paper analyzes the students’ perception toward synchronous and asynchronous learning in speaking skill during pandemic Covid-19. There were 20 students of Intensive English Class at Language Development Unit at UIN Antasari Banjarmasin which were interviewed to know their perception on the synchronous and asynchronous learning in English speaking class. The data were analyzed descriptive-qualitatively. The result found that the students felt more anxious to speak English in synchronous learning mode by using teleconference application such as zoom and Google meet than to speak in asynchronous learning mode by using video recorder.
INTERACTIVE METHODS IN INFORMATION TECHNOLOGY AND COMPUTER MODELING TRAINING

21st century children grow up in an environment full of different technology, they are used to getting the information they need, with the help of information and communication technologies, their normal daily life includes the obligatory participation of some kind of multimedia device or even a few.When these same children become students, they have certain expectations that this situation will continue in the school institution. They expect that their training will be filled with all kinds of technologies to upgrade, supplement and modernize it.In order to meet these expectations, primary school teachers are forced to constantly improve their professional qualifications, to improve the level of their knowledge, skills and competencies. However, this requires serious additional work on their part, as well as some material security, which in some cases may not be available.The application of interactive methods is one of the solutions that teachers can apply when they want to enrich and upgrade the learning process, as well as increase the motivation of students to participate in it. In the literature can be found descriptions and information about a large number of different types of interactive methods that do not require much prior training on the part of the teacher, as well as additional material security, but this does not mean that a large percentage of educators apply them.It is this fact that provoked us to conduct a study of the actual implementation of interactive methods, specifically in the training of Information Technology and Computer Modeling. Our aim was to study not only the use of this type of methods by teachers, but also their opinion on the positive and negative effects of their use, the need for innovative methods, their selected software solutions and methodologies, and the availability of the necessary condition for their introduction into the learning process. We were also interested in the level of education, which according to the teachers is the most suitable for the use of interactive methods.