Reviewerly/exHarmony huggingface dataset:
Recognition of Spam Messages Based on Text Mining

Abstract With the rapid development of science and technology, the application of artificial intelligence technology is becoming more and more extensive. The maturity of artificial intelligence technology is inseparable from big data and machine learning. Big data is the foundation of artificial intelligence, while machine learning is the core. To mine the value hidden in big data, in order to achieve text classification, data prediction, and provide strategic decision basis, we need the power of Machine Learning. This article will introduce the classic algorithm in machine learning, Naive Bayes, KNN nearest neighbor, and support vector machine algorithm, and apply them to text mining of spam text sets. It shows that Machine Learning is the fundamental way to make machines as intelligent as humans.
The Influence of Oral-Cued Retell Strategy in Teaching Students’ Speaking Skill ( An Experimental Research at first Grade of MA ANNIDA Islamic Boarding School Jayanti Kab.Tangerang Banten )

Alief Achrun Nazar, 142301752, 2018. The Influence of Oral-Cued Retell Strategy in Teaching Students’ Speaking Skill ( An Experimental Research at first Grade of MA ANNIDA Islamic Boarding School Jayanti Kab.Tangerang Banten )Speaking using foreign language well, especially English is still a problem for some students / language learners in Indonesia, especially for students in first Grade of MA ANNIDA Islamic Boarding School Jayanti Kab.Tangerang Banten. They are still confused and the biggest problem of students is less of confidence in using and practicing English. This research is to determine whether the students’ speaking skill can be improved by using Oral-Cued Retell Strategy or not. The researcher used Quantitative Research with Quasi-experiment type to determine the influence of Oral-cued retell strategy in teaching students’ speaking skill. This is involved two classes (experimental class and control class), each class consist of thirtieth students. Then from findings above, it can be concluded that Oral-cued retell strategy has an influence in improving students’ speaking skill especially students become more interested and more confident in practicing their daily English.The result of this research shows that the students speaking abilities who use cued retell strategy achieve better performance than those who do not use Oral-cued retell strategy The result of the data analysis is using t-test the value of is 5,27, the degree of freedom 58. In the degree significance 5% = 1,67 in degree of significance 1% = 2,39. After that the writer compared the data with (t table) both in degree significance 5% and 1%. Therefore = 5,27 > 1,67 in degree of significance 5% and = 5,27 > 2,39 in degree significance 1%. is bigger than it means there is significance effect of using Oral-cued retell strategy to improve students’ speaking skill.
Using GLOBE observer mobile application in secondary school learning activity

As technology plays a crucial role in daily life, IPST has designed GLOBE activity using GLOBE Observer mobile application. In order to integrate the application into this activity, we designed activity for students to take measurements of tree height through application together with Green Up and Green Down protocols through lecture and hands on activities. According to the interview of nine teachers from five schools about the Green Up activity, it shows that 72% of students answered questions correctly in data sheet while, on the Green Down activity, 89% of student specified color of Paper-tree leaves correctly using GLOBE color guide. During fieldwork activity to investigate and observe characteristics of tree leaves and tree height, it is found that 63% of students be able to send data through GLOBE observation application. All the teachers agreed that the GLOBE tree application menu is easy to use and free of charge. Moreover, all related materials are easy to prepare. However, the limitation of activity is that the application is not compatible with some devices. To gain more accurate and precise data, students need to practice measurement beforehand.
Clifton Fowler Library: Computer Science, Networking, & Cyber Security: Computer Science, Networking and Cyber Security Related Guides

Collection of resources for Computer Science, Networking and Cyber Security (articles, books, and websites) Business Related Guides
LibGuides: Welcome, Kids! : Cool Collections

A one-stop-shop for our youngest patrons to learn about all the great benefits of being a library member!
Artificial Intelligence and The Future of Literary Works

This chapter focuses on literary works as a way to ground the discussion since books have always been at the core of copyright protection. It concludes that opt-out automated collective licensing systems may be the only workable solution for striking the balance between developments in AI research and application and the rights of creators whose works are used to train AI machines. The factor would favor a fair use finding, since entire works are copied, and for most literary works, the second factor should also weigh against fair use. The Digital Millennium Copyright Act of 1998 was a sweeping piece of legislation, but the part that has caused the most heartburn for copyright owners is the safe harbor provision that effectively immunizes internet intermediaries such as online platforms for the copyright infringement perpetrated by their users, provided the platforms comply with certain obligations.
Collective and individual use of smartphones : The case of Swedish upper secondary Building and construction and Hairdresser education

Collective and individual use of smartphones : The case of Swedish upper secondary Building and construction and Hairdresser education
Improved K-means Using an Integration of Density based and Genetic Algorithm based Model

In the data oriented world that we live in, many clustering algorithms exist but one that has been widely studied and used is K-means. K-means is a well-known clustering algorithm, however, it is not without its limitations. A few of its limitations have been identified, as well as ways to improve it so as to make it more efficient. The first problem identified is that the optimal K value must be known beforehand. If a bad value is selected, it will result in poor clustering. This is achieved by a method that uses density plots to determine the best K value. The next problem that is looked into, is ways to optimize the initial centroid selection process and thus improve efficiency of the algorithm as a whole. This is done by using an evolutionary algorithm called genetic algorithm. This enhanced version is then tested on benchmark clustering datasets and artificially generated datasets. Afterwards, it is applied to a dataset consisting of geographical coordinates of taxi pickup locations to identify hotspots.
Perancangan Sistem Informasi Monitoring Produksi di CV. Savana

Abstract — Monitoring is defined as a cycle of activities that includes the collection, review, reporting, and action of information on a process that is being implemented and can provide information that aims to determine the suitability of the process has been running. CV. Savana is a manufacturer, exporter, supplier of rattan furniture located in Cirebon. Rattan furniture products produced are sold to many importers, wholesalers, stores, distributors and retailers in the world. However, the obstacle that occurs is that there is a discrepancy in the data when there is a change in demand from the buyer, for example changes in the amount of goods. Because the system is not yet integrated, so the data and information obtained by each part are less accurate, such as the availability of raw materials in the sub-contractor and the information obtained by the production admin regarding the production process at the sub-contractor, which is less detailed so that it affects the production process and delivery of goods to the buyer.Therefore, to help overcome the problems that occur in the production process at CV. Savana, the need for a production monitoring information system.
Procedurally generating an initial character state for interesting role-playing game experiences

Procedurally generating an initial character state for interesting role-playing game experiences
Monetary compensation 2.0: investigating the efficacy of crypto compensation

Monetary compensation is one of the key recovery tools in improving customer satisfaction following a service failure [1]. Majority of studies have looked at different levels of compensation (some vs. none or partial vs. full compensation) as well as different types (e.g., cash vs. voucher) [2, 3]. However, with the rapid advancement and implementation of technology in various sectors, academic research has not kept pace with the potential implication of such revolutionary technologies such as blockchain and particularly, the adoption of cryptocurrencies. Bitcoin, which is one of the most popular cryptocurrencies has found its way as an alternative form of payment in retail and hospitality sectors. For instance, there are various companies accepting Bitcoin as payment for purchasing an airline ticket, booking hotels and holidays, or even buying food. Though there is little doubt of the potential for cryptocurrency to revolutionize payment, there is still little business related research on the phenomenon and none in the area of service recovery compensation. Extending previous studies on service recovery, we provide the first examination of crypto-compensation, to shed initial light on the following questions: should firms offer crypto-compensation instead of voucher or cash? And does financial risk aversion moderate crypto-compensation effectiveness?
GKE Monitoring Using Prometheus

This chapter provides hands-on steps to guide you through the use of Prometheus for GKE monitoring. In addition, it covers the following:
LibGuides: Library Research Skills: Finding Print Books: Types of Searches

This LibGuide has the same content as the Finding Print Books module your professor may have in Canvas.
Modelo de administración de identidad digital (IdM) sobre blockchain para la mitigación del riesgo por suplantación en sistemas e-banking

The modern society increasingly depends on technology and the internet for your development and normal operation. For 2019 more than 4,131 million of users were connected to the internet in the world and the same way in Colombia more than 19 million people contracted a subscription to this medium. Also, for 2019 the internet became the most used transactional channel in the country, displacing traditional channels such as bank branches and ATMs. However, along with this growth, cyber risks also increase and one becomes the concern of state entities, private companies and research sectors: the theft of credentials and their subsequent use for identity theft. We are then faced with a global challenge - that is particularly critical for the financial sector: Developing new models for identity management (IdM) by reducing the risk of identity theft for end users.The emergence of new technologies such as blockchain, open new possibilities that allow to rethink traditional IdM models, taking advantage of features such as scalability, transparency, cryptographic security and immutability of this block system.This work investigated and consolidated the main techniques used for credential theft today, techniques that expose the weaknesses of traditional IdM systems. At the same time, the emergence of new approaches and solutions for managing digital identity using blockchain technology was deepened. Thanks to this, a new IdM model on blockchain called self-sovereign IdM with guarantor was formulated, which, when subjected to a comparative evaluation against the 3 IdM models currently used by the main banks in the country, confirmed its lower level of vulnerability in the face of attack techniques for the theft of credentials used by cybercriminals.
Detecting Offside Position using 3D Reconstruction

With the increased number of technical innovations in soccer and the progress in the field of AI, this thesis investigates the possibilities to detect if a player is in offside position using deep learning and video recordings from soccer games. A method to create a 3D reconstruction of the players in the scene is proposed and evaluated. The arguments for using a 3D reconstruction is that it introduces a volume to the players which hopefully result in increased quality of offside decisions. A system for detecting offside position is proposed consisting of an object detector, a pose estimator, a mesh estimator and a team classification. The position of the players are estimated by minimizing the reprojection error between the 2D pose and the 3D pose, further on the reprojection is weighted using the confidence of each predicted 2D joint. The system is able to detect players in offside position with a precision of 60% and a recall of 97%. It is also shown that by weighting the reprojection error the precision of detected players in offside position is increased from 5\% to 60%. It is also shown that reconstructing the scene increases the average F1 score from 0.82 to 0.86. (Less)
FACE RECOGNITION FOR THE AUTOMATIC ATTENDANCE MANAGEMENT SYSTEM

Face Recognition is a currently developing technology with multiple real- life applications. The goal of this Thesis is to develop a complete Face Recognition system. The system uses Convolutional Neural Networks in order to extract relevant facial features. These features allow to compare faces between them in an efficient way. The system can be trained to recognize a set of people, and to learn in an on-line way, by integrating the new people. Face recognition system is one of the biometric information process its applicability is easier and working range is larger than others .The face recognition is live acquired images without any application field in mind .process utilized in the system are White Balance correction ,skin like region segmentation .facial feature extraction and face image extraction on a face Candidate .The face one of the easiest ways to distinguish the individual identify each other .Face recognition is a personal identification system that uses personal characteristics of a person to identify the person’s identify. KEYWORDS:-Face Recognition, Facial Attendance, Automatic Attendance, Face Detection.
Bitcoin : A study on the determinants of the Bitcoin price development

Bitcoin is a new evolutionary development within the internet and payment system. Its price has a high volatile nature what brings a lot of attention to this cryptocurrency. This paper investigates ...
Microblog User Geolocation by Extracting Local Words Based on Word Clustering and Wrapper Feature Selection

Existing methods always rely on statistical features to extract local words for microblog user geolocation.There are many non-local words in extracted words, which makes geolocation accuracy lower.Considering the statistical and semantic features of local words, this paper proposes a microblog user geolocation method by extracting local words based on word clustering and wrapper feature selection.First, ordinary words without positional indications are initially filtered based on statistical features.Second, a word clustering algorithm based on word vectors is proposed.The remaining semantically similar words are clustered together based on the distance of word vectors with semantic meanings.Next, a wrapper feature selection algorithm based on sequential backward subset search is proposed.The cluster subset with the best geolocation effect is selected.Words in selected cluster subset are extracted as local words.Finally, the Naive Bayes classifier is trained based on local words to geolocate the microblog user.The proposed method is validated based on two different types of microblog data -Twitter and Weibo.The results show that the proposed method outperforms existing two typical methods based on statistical features in terms of accuracy, precision, recall, and F1-score.
LibGuides: OneSearch: The Library Discovery Tool: Viewing Your Library Account

This guide is here to help the Cal State LA campus become more familiar with the library discover tool and how it works.
Energy Management Techniques for Cloud Based Environment

Cloud Computing has the facility to transform a large part of information technology into services in which computer resources are virtualized and made available as a utility service. From here comes the importance of scheduling virtual resources to get the maximum utilization of physical resources. The growth in server’s power consumption is increased continuously; and many researchers proposed, if this pattern repeats continuously, then the power consumption cost of a server over its lifespan would be higher than its hardware prices. The power consumption troubles more for clusters, grids, and clouds, which encompass numerous thousand heterogeneous servers. Continuous efforts have been done to reduce the electricity consumption of these massive-scale infrastructures. To identify the challenges and required future enhancements in the field of efficient energy consumption in Cloud Computing, it is necessary to synthesize and categorize the research and development done so far. In this paper, the authors prepare taxonomy of huge energy consumption problems and its related solutions. The authors cover all aspects of energy consumption by Cloud Datacenters and analyze many more research papers to find out the better solution for efficient energy consumption. Keywords: Cloud computing, Collocated virtual machines, Live migration, Load balancing, Resource scheduling
Aplikasi Mobile untuk Pencatatan Keuangan Pengeluaran Biaya dan Penerimaan Dana pada Usaha Tani Padi (AKUPADI)

The level of income of farmers is influenced by several components, namely the amount of production, production costs, and product selling prices. In knowing the level of farmers' income, records management is needed in the form of financial statements that can be used as a reference in managing all production inputs. AKUPADI mobile application was developed using the waterfall method by providing several features that can be used to assist farmers in carrying out rice farming activities. This application was built using language that is easily understood by farmers. Features provided by the AKUPADI application are recording expenses, recording receipt of funds, displaying transaction history, displaying reports, and managing production input data.
Textbooks for the New Ukrainian School as a means of effective educational communication: discourse analysis and problems of the culture of the edition

The purpose of the study, which we started in October 2018 with the support of the Ministry of Education and Science of Ukraine and the intergovernmental Ukrainian-Finnish project Learning together, is to analyze the quality of modern textbooks for the first grade of the Ukrainian School, to identify outdated scientific paradigms, to identify and systematize cultural problems of textbook publication, which should be taken into account during the editorial and publishing of textbooks for the second and third grades.Methodology. At the initial stage of the study, a bibliographic method was used for the identification and systematization of scientific sources, normative legal documents on the problems of textbook creation.The use of methods of discourse analysis, logical, semantic, context analysis of text and visual components of textbooks for the first grade of the Ukrainian School made it possible to identify the problematic aspects of the culture of textbook publication.Typical flaws in the culture of textbook publication for the Ukrainian School are systematized using methods of scientific generalization and classification.The results of the research showed a number of problems: visualization of outdated Soviet discourse, systemic errors, consistency and logic of presentation of the material, fairly low linguistic culture of publications, and sometimes unsatisfactory quality of artistic design. The solution of these problems requires a complex, systemic and integrative approaches. This includes the training of editors, publishers, authors, the formation of their high social responsibility, the creation of a single scientific and informational space for authors, reviewers and editors based on the leading publishing houses and academic departments of publishing and editing, the organization of seminars, trainings, summer/winter schools, etc. Such work has already begun within the preparatory stage of the international project Finnish support for a Ukrainian School. The results of the research were used during the All-Ukrainian scientific and practical seminar New textbook for the Ukrainian School: Requirements, criteria for evaluation, registration organized by the Institute for the modernization of the content of education for publishers who worked on textbooks for the second grade of the Ukrainian School (November 22, 2018), training for experts who assessed the textbook for the second grade of the Ukrainian School (January 21-23, 2019) and training sessions for publishers of textbooks for the Ukrainian School (March 12-15, 2019), prepared by using experts from the Ukrainian-Finnish project Learning together.
Understanding aarogya setu: navigating privacy during a pandemic proves to be tricky

Upasana Sharma (Carnegie India) writes that Aarogya Setu, India’s contact tracing application, raises many privacy concerns. And while making the app open source is the right step in ensuring a transparent framework, there is more work to be done in ensuring increased user security and privacy.
Investigating and Evaluating Software Ecosystem Modelling in Practice in a Tier-2 Vehicle Telematics Company

Although different ecosystem modelling techniques exist, it is difficult to assess howused these are in practice among software companies. In this design science study,software ecosystem practices of a software company in the automotive domain wereanalysed; according to the findings, there are different perceptions of an ecosystemamong management and developers, and there are no formalised modelling techniquesbeing used in the company. The study was conducted in three iterations;in the following two iterations, two modelling techniques were analysed, identifyingthree different points of improvement for one of them. The technique for whichthe changes were proposed was the technique favoured by the participants of thestudy. The findings indicated that, while participants did not have a consistent viewof which changes would provide more benefit to the modelling technique, many ofthem saw possible use cases for ecosystem modelling using the presented modellingtechnique. These use cases were consistent with the perceptions that the individualshad about software ecosystems and showed that they believed modelling techniquesto be potentially useful for the company, even if they were not currently using them.
Use of autoencoders as a generalization method for anti-spoofing classification

Computer vision is one of the hot topics nowadays when talking about artificial intelligence, covering a wide range of problems under its domain, from document verification to object detection. One of these problems consists of detecting spoofing attacks, masquerading as a registered user in a face-recognition system, gaining illegitimate access and advantages, used in face-recognition payments, phone unlocking, workers checking –in… When training models focused on solving this kind of problems, one of the main concerns is the data we have to deal with due to its small variety, leading to generalization problems. Some of the main approaches that try to tackle these overfitting issues include dropout techniques, model variations or adding some kind of regularization. While in general the way of adding regularization is by introducing a regularization parameter in the objective function, in this thesis we will be presenting another equivalent regularization algorithm.