Reviewerly/exHarmony huggingface dataset:
A-GNN: Anchors-Aware Graph Neural Networks for Node Embedding

With the rapid development of information technology, it has become increasingly popular to handle and analyze complex relationships of various information network applications, such as social networks and biological networks. An unsolved primary challenge is to find a way to represent the network structure to efficiently compute, process and analyze network tasks. Graph Neural Network (GNN) based node representation learning is an emerging learning paradigm that embeds network nodes into a low dimensional vector space through preserving the network topology as possible. However, existing GNN architectures have limitation in distinguishing the position of nodes with the similar topology, which is crucial for many network prediction and classification tasks. Anchors are defined as special nodes which are in the important positions, and carries a lot of interactive information with other normal nodes. In this paper, we propose Anchors-aware Graph Neural Networks (A-GNN), which can make the vectors of node embedding contain location information by introducing anchors. A-GNN first selects the set of anchors, computes the distance of any given target node to each anchor, and afterwards learns a non-linear distance-weighted aggregation scheme over the anchors. Therefore A-GNN can obtain global position information of nodes regarding the anchors. A-GNN are applied to multiple prediction tasks including link prediction and node classification. Experimental results show that our model is superior to other GNN architectures on six datasets, in terms of the ROC, AUC accuracy score.
School Course on Information Security: Structure and Content

The course is designed for conducting lessons on information security of students on the Internet and reflects the current issues of safe work with personal information, messages and calls on a mobile phone, e-mail, information and communication resources on the Internet for access to resources for leisure, search for news, educational, educational information, communication in social networks, receiving and transferring files, placing personal information in collective social services. The course is based on technical, ethical and legal standards of information security compliance established by regulatory and law enforcement agencies, as well as practical recommendations of leading IT- companies and mobile operators of the Russian Federation.
Data Mining and Association Rules to Determine Twitter Trends

Opinion mining has been widely studied in the last decade due to its great interest in the field of research and countless real-world applications. This research proposes a system that combines association rules, generalization of rules, and sentiment analysis to catalog and discover opinion trends in Twitter []. The sentiment analysis is used to favor the generalization of the association rules. In this sense, an initial set of 1.6 million tweets captured in an undirected way is first summarized through text mining in an input set for the algorithms of rules and sentiment analysis of 158,354 tweets. On this last group, easily interpretable standard and generalized sets of rules are obtained about characters, which were revealed as an interesting result of the system.
A visual introduction to digital and social media marketing

Strategic approaches to digital marketing recognise clearer differentiations that move beyond broad brush identifications of ‘users’. In combination, the organisation, the buyer persona and the several elements of digital marketing strategy represent the Buyer Persona Spring. The more integrated use of data throughout the organisation is the key driver to increasing digital maturity. Even traditional business models, for example, taxis and bed and breakfasts, have felt the influence of digital technology through the impact of the Uber and AirBnB apps and their associated business models. With the business models of these disruptors built around the sharing economy and social networking channels, the challenge they present to other models is the way they resist being pinned down to conventional definitions or practices. Increasing business transparency, innovative business models and the use of sharing and crowdsourcing challenge existing labels and traditional definitions requiring deeper reflection and more mature responses from an organization.
CCSDS-MHC For Lossless Hyperspectral Image Compression on Beaglebone Black Board

This project is to achieve a lossless hyperspectral image compression of satellite imagery by the implementation of the Consultative Committee on Space Data Systems (CCSDS) algorithm named CCSDS Lossless Multispectral and Hyperspectral Image Compression (CCSDS-MHC) on Beaglebone-Black board (BB-Black). 224 and 196 spectral bands of AVIRIS and Hyperion datasets, respectively are used. The BB-Black board is used to implements and optimizes the CCSDS Lossless Multispectral and Hyperspectral Image Compression (CCSDS-MHC) algorithm. As for the result, the ratio for the BB-Black board execution time compared to the desktop is in the range of 10 to 25 times longer. The losslessness is verified by referring to the desktop program. The compression ratio is in the range of 2.0 to 5.0.
VUW students translate Hone Tuwhare

The translation of Hone Tuwhare’s poem ‘Mauri’ into Italian was part of an assignment of Victoria University course Ital 301 which I taught in the first trimester 2019. We have chosen a few bright versions for publication in Neke.I would like to express my gratitude to the poet’s son, Rob Tuwhare, and to Hone Tuwhare Poetry for their kind permission to reproduce the original text.Antonella Sarti Evans
Влияние гиперпараметров нейронной сети на её численную обусловленность

In this paper, the task of assessment of numerical conditioning of multilayer perceptron, forecasting time series with sliding window method, has been considered. Performance of the forecasting perceptron with various hyperparameters sets, with different amount of neurons and various activation functions in particular, has been considered. Main factors, influencing on the neural net conditioning, have been revealed, as well as performance features, when using various activation functions. Formulas for assessment of condition numbers of individual components of the forecasting perceptron and of the neural network itself have been proposed. Comparative analysis of results of training the forecasting perceptron with various hyperparameters on modeled time series has been performed. Conditions, providing the best stability and conditioning for the neural network, have been formulated.
Features of development of electronic library information systems of universities

The article describes the selection criteria for electronic library systems and the requirements for them. The main problem of the systems that are offered for purchase to universities is analyzed and summarized. The criteria that electronic libraries must meet, the basic principles of building and developing own electronic library and information systems of universities are considered. The types of users who can work with the system, the content that the electronic library should contain, are described. Structural schemes of the electronic library system of the university and its elements are given. The schemes meet regulatory requirements and take into account the specifics of the work of higher educational institutions. The basic elements and modules of the electronic library system, their main functionality and content components are presented. The approach proposed by the author of the article will allow universities to develop and organize electronic library systems within their educational institution.
Perancangan Aplikasi Enkripsi Pada File Suara Menggunakan Algoritma Spritz

Issues Security and confidentiality of data is one important aspect in terms of information exchange. One solution to maintain security and confidentiality in the process of sending files with encryption techniques as encryption keys on voice files. This study describes developing cryptography (encryption and decryption) that applies the Spritz algorithm. But not all developments in communication technology have a positive and beneficial impact. One of the negative effects of sound files is data tapping, which is one of the most feared problems by network users and voice files. This research resulted in an application program aimed at preventing the security of sound files on storage media. in making this application, the method used is the Spritz algorithm, because it is very suitable for the security of voice files that result in the completion of the encryption and decryption process. This application was created with visual basic 2008 software and the creation of a file security application using encryption and decryption processes using the Spritz algorithm is expected to overcome these problems. The format used in making this application encrypts and decrypts the sound files that have an extension. WAP, and MP3
Perancangan Iklan Layanan Masyarakat Bahaya Cybercrime dalam bentuk Motion Graphic

. Motion Graphic is a trendy audio visual media to inform nowadays.With the massive technology growth people are addicted to internet.Everybody is able to use internet start with kids and until elderly are able to use internet.Because of that some of villain take the advantages from it,they use internet for robbing people without making any physical contact to the victim.So the design of this public advertise is to give warn message to all people that using internet to be warn from cybercrime.
So, What is White Hat Hacking?

Abstract Justin Shaw Grey, Sales Director of Synack, spoke to Johanna Hamilton AMBCS about the competitive world of international pen-testing, finding vulnerabilities in programs and selling the concept of white hat hacking to a company board.
Prediction of Shear Characteristics of Unsaturated Soil Based on BP Neural Network

The prediction model of shear strength parameters of unsaturated soil based on indoor test data is established by using BP neural network. Five kinds of network models with different number of hidden layer nodes are trained and studied, and the best network model is selected to conduct the prediction. The results show that the optimal BP network model is a single hidden layer structure of 8-16-2. Using this model to predict, the correlation coefficient and regression coefficient between the predicted value and the measured value are high, and the predicted result is reliable, so the method has certain practicability.
The PRNU Algorithm of Video Forensics

The A video sequence provides more proof of an occurring event than a photo or a group of photos. Hence it is important to identify the source of the video. In this paper, we explore how the Photo Response Non-Uniformity (PRNU) noise is useful for the detection of source cameras- Metadata of a Camera. With this method, we aim to determine whether the video originated from the given camera or not.
Authorship Attribution in Latin Languages using Stylometry

In this paper we presented a computational approach to authorship attribution in a multilingual environment, based on latin languages. Initially, we defined the databases of literary texts, written by consecrated authors of Portuguese, Spanish and French literature. Subsequently, we established a set formed by groups of stylometric characteristics, which are: morphological, flexors, syntactic and auxiliary. The main objective is to extract from the grammatical structures of the sentences, the stylometric pattern of each author. We perform experiments with author-dependent approach, using verification and identification strategies. In the classification process we use the Support Vector Machines - SVM, with a linear kernel.
IMPLEMENTASI METODE WATERFALL DALAM MEMBANGUN MANAJEMEN KESISWAAN BERBASIS WEB PADA SUKU DINAS PENDIDIKAN WILAYAH I KOTA ADMINISTRASI JAKARTA TIMUR

Student data has an important role, especially in an educational institution. Because the data can be used as a reference for planning further education programs. The Education Office is a Work Unit of the Education Office in the City Administration in the implementation of educational activities in the City Administration Area. In this case the Education Office Tribe does not have the authority to manage student data which causes the institution must take a long time if at any time such data is needed because the Education Department Tribe must coordinate with the Implementing Unit (Satlak) to request data from the school, not yet a database for student data on a periodic basis, as well as frequent differences in data between one data with another. In this case the researchers used the waterfall method for making student management systems, and used UML (Unified Modeling Language) in designing student management systems and using SWOT analysis methods (Strength, Weakness, Opportunity, Threat) to analyze strengths, weaknesses, opportunities and threats. Based on the results of research from the student management system it can be concluded that this system can facilitate inter-educational institutions in monitoring student data and transfer student data that will be transformed into information that can be useful for those who use it.
Transformasi perpustakaan dalam rangka mewujudkan layanan perpustakaan yang inklusif: studi kasus di perpustakaan umum daerah kabupaten pulan pisau

Library has a strategic role as a lifelong education whose can optimizing the services for all of people to developing personal potentional. The library also has a role as a leading sector to creating a literate society. Literate society in one side and an economic development in another side are two related variables. The regional government of Pulang Pisau Regency has colaborate with the National Library of Indonesia to reinforce the library by transforming library services based on social inclusion. Social inclusion based library are a library transformation that serves the information needs of all of the visitors. Social inclusion based library are also committed to meet the information needs of people with the information that can improve cognitive abilities and stimulating welfare improvement with library resources. This article discusses the transformation made by Pulau pisang regency public library to realize library services based on social inclusion.
Incorporation of Language Discriminative Information into Recurrent Neural Networks Models to LID Tasks

Language Identification (LID) is an essential research topic in the Automatic Recognition Speech area. One of the most important characteristics relative to language is context information. In this article, considering a phonotactic approach where the phonetic units called “phone-grams” are used, in order to introduce such context information, a novel technique is proposed. Language discriminative information has been incorporated in the Recurrent Neural Network Language Models generation (RNNLMs) in the weights initialization stage to improve the Language Identification task. This technique has been evaluated using KALAKA-3 database that contains 108 h of audios of six languages to be recognized. The metric used in this work has been the Average Detection Cost metric Cavg. In relation to the phonetic units called “phone-grams” used in order to incorporate context information in the features used to train the RNNLM, it has been considered phone-grams of two elements “2phone-grams” and three elements “3phone-grams”, obtaining a relative improvement up to 17% and 15,44% respectively compared to the results obtaining using RNNLMs.
Need analysis in the development of teaching materials with problem solving-collaborative models in quantum physics courses

Abstract This study aims to analyze preliminary data on the conditions of quantum physics lectures as a necessity in developing teaching materials. This research is the initial stage of research and development, namely preliminary research. Data collected using interviews with lecturers, questionnaires to students and study documentation. Data analysis techniques used in the form of descriptive statistical analysis. From the data analysis that has been done it can be stated that the available quantum physics teaching materials have not varied. Second, the assignments given in lectures on quantum physics have been able to help students understand the material. Third, students have sufficient potential in understanding the material, but the percentage of students who have ideas in solving problems and who are able to correct answers from friends, want to work collaboratively and who actively ask questions is still low. For this reason, it is necessary to develop media and teaching materials to improve the lecture and collaborative processes of students.
Application of Fossil and Artefact Collection in The Human Reservation Center Sangiran of Sragen Krikilan Cluster Based on Android

Sangiran is the biggest early man site in Indonesia which has an important value such as human evolutions, culture, early fauna, and its environments. The evidence of the living past of early man sees through fossil collection, artifact, and environment. Sangiran collections save in Sangiran Early man Museum, under the management of the Preservation Center of Early Man Site Sangiran. Sangiran site is recognized as a World Cultural Heritage that has a problem in disseminating information about its important value. There are still many people who don't know about the important value of Sangiran.Related to the problem, the writer arranges an application that aims to make it easy for the community in getting information about the collection in the Preservation Center of Early Man Site Sangiran quickly, simple, and informative. This application is designed with the Unified Modeling Language (UML) method. In making this application, the writer uses software Construct 2 that is editor of game HTML5 based developed by Scirra Ltd who maximizes the editor's visual function and behavior-based logic system.The result of the research, the writer makes a mobile informative system that is "Application of the Introduction of Fossil and Artefact Collection in the Preservation Center of Early Man Sangiran Site Cluster Krikilan Based on Android". The advantage of this system is it can be an introduction media by the Preservation Center of Early Man Site Sangiran which only used with Android, meanwhile the weakness is it can only be operated on Android, not yet able to ios and desktop.
Real Time Identification of American Sign Language for Deaf and Dumb Community

The only way for deaf and dumb for communication is based on sign language which involves hand gestures. In this system, we are working on the American Sign Language (ASL) dataset (A-Z), (0-9) and word alphabet identification escort by our word identification dataset of Indian Sign Language (ISL). Sign data samples to be making our system more faultless, error free, and unambiguous with help of Convolutional Neural Network (CNN). Today, much research has been going on the field of sign language recognition but existing study failed to develop trust full communication interpreter. The motivation of this system is to serve a real-time two-way communication translator based on Indian Sign Language (ISL) with higher precision, efficiency, and accuracy. Indian Sign Language (ISL) used by Deaf-mute people’s community in India, does have adequate, delightful, acceptable, meaningful essential and structural properties.
Credit Card Fraud Detection Using Meta-classifiers Consisting of Semi-supervised and Supervised Algorithms

Usage of credit cards has grown over the years and so have the fraudulent transactions associated with them. It is imperative for every organization to have an efficient fraud detection system. This paper proposes two level meta-classifiers which use One-Class SVM, a semi-supervised algorithm in their first phase and supervised algorithms like logistic regression and random forest in their second phase. Using classifiers of this kind enables the fraud system to identify as many fraudulent transactions as possible and keeps the number of false positives to a minimum value, and this ensures minimum loss of money as well increased customer satisfaction.
Identify the Candidate Hunks Containing Statement Encapsulation Patterns

Software version changes will result in the submission of a large number of change codes, and multiple change patterns are embedded in the change code. Identifying these change patterns helps to understand the details of the software changes. This paper examines the identification of candidate hunks for this change pattern in a common statement or sequence of statements moving to one or more different grammatical entities. For the existing code cloning tool Simian, the recognition rate of candidate hunk is not high for this statement encapsulation pattern. This paper proposes a candidate hunk recognition algorithm based on the longest common subsequence algorithm. The algorithm uses a text-based differential analysis tool to get the code change block hunk of the version before and after the code change. The candidate hunk is identified by combining the features of the statement encapsulation pattern candidate hunk. The algorithm was experimentally verified on four open source projects. Experimental results show that the algorithm has higher accuracy than Simian tools.
Aesthetics of Interaction on Virtual Reality with Educational Games Content

The digital and virtual era creates a dependency between arts, science and technology. Knowledge and applications, currently, can no longer be separated, so there are overlaps between these concepts. In terms of interactive art, aesthetics no longer only arises because of its visual and sound beauty. This study investigates the diversity of aesthetic in virtual reality, especially with educational game content. This paper describes the aesthetic elements that occur in the experience of interaction through educational games. The case study of existing VR projects led this investigation of the aesthetics of interaction. The previous projects will be analysed for describing the aesthetics of interaction elements. We use the MDA framework (Mechanics, Dynamics, and Aesthetics) for study the learnable material as an element of aesthetic in virtual reality. Finally, we conclude that educational aspect potentially provides aesthetic elements in the play experience of the games with virtual reality technology.
PREDIKSI FINANCIAL DISTRESS MENGGUNAKAN MODEL NEURO FUZZY DAN RASIO ALTMAN

Financial distress is a condition of decline in corporate finance before business failure. This failure is closely related to insolvency, where the company has failed in carrying out its operations for profit. Financial distress prediction methods have long been developed by researchers in the field of accounting and finance using Multiple Discriminant Analyst (MDA). A common method is that the Altman model is used to predict financial distress one year in the future, this is as an early warning of the company's financial condition .The purpose of this study is to develop a data mining application neuro fuzzy algorithm model using the Altman model input data ratio to predict the company's financial distress for the next few years optimally. The data used are financial statements from 45 LQ45 Issuers on the Indonesia Stock Exchange (IDX) in 2013-2017. The initial process of calculating the balance sheet and profit (loss) financial statements through the Altman model ratio to get zscore values of three categories (safe, gray and distress). The values are sorted by four backward periods as input data to the model. Functional tools from the Matlab GUI program will be used for the formation, training and testing of the neuro fuzzy structure of the ANFIS 4MFs model. Furthermore, the predicted value of the model is compared with the value of the calculation of the target Altman ratio. The final results show that the ANFIS 4MFs model can provide highly optimal predictive values close to the average target ratio value of 100% in the membership functions of Gauss, Trapezoid, and G-bell.