Reviewerly/exHarmony huggingface dataset:
Graph-Time Convolutional Neural Network: Learning from Time-Varying Signals defined on Graphs

Time-varying network data are essential in several real-world applications, such as temperature forecasting and earthquake classification. Spatial and temporal dependencies characterize these data and, therefore, conventional machine learning tools often fail to learn these joint correlations from data. On the one hand, hybrid models to learn from time-varying network data combine several specialized models able to capture these dependencies separately, thus ignoring their joint spatio-temporal interactions. On the other hand, state-of-the-art approaches for jointly learning time-varying network data do not exploit the useful prior provided by a graph-time product graph. This prior structural knowledge can aid learning and help the models improve their performance. For this reason, we propose a novel neural network architecture to learn from time-varying network data using product graphs and graph convolutions, thus exploiting this prior during learning. In particular, our architecture (i) learns the most suitable graph-time product graph to represent the time-varying network data and model the graph-time interactions; (ii) performs graph convolutions over this product graph to learn the graph-time interactions from data; (iii) employs graph-time pooling to reduce the dimensionality over layers. To the best of our knowledge, no research has yet attempted to capture spatial and temporal dependencies using graph convolutions over product graphs. Results on synthetic and real-world data show that the proposed method is useful in learning from time-varying network data for both regression and classification tasks. For classification, we cure a real-world dataset for earthquake classification and compare the proposed approach with state-of-the-art models. Results indicate that graph-aware models outperform graph-unaware models on this task. For regression, we evaluate the proposed method on two real-world temperature datasets and compare our architecture with graph-aware and graph-unaware models. Results on the smaller dataset show that linear models outperform neural-network models. On the larger dataset, we find that prior knowledge about graph-time interactions seems to be less beneficial in case of abundance of data. For the synthetic experiments, we find that (i) learning the structure of the graph-time product graph from data improves the performance compared to adopting a fixed type of product graph; (ii) learning sparser graph-time product graphs further improves the performance; (iii) the proposed graph-time pooling technique contributes to the model's generalization capabilities.
Data Processing and AI

Today, Artificial Intelligence (‘AI’) is at the heart of many applications. Video recognition technology can lip read speech and respond to speech; character recognition systems can decipher written script; photo software identifies people in pictures; there is near real-time translation from multiple languages at your fingertip, self-driving cars and applications for medical diagnosis could soon become common and AI is behind the rise of the robots at manufacturing and distribution facilities.
PERAN PUSTAKAWAN DAN MASALAH KECURANGAN AKADEMIK DI PERGURUAN TINGGI (Studi Kasus di Universitas Muhammadiyah Ponorogo)

Being a librarian is not an easy job. Especially in the information age like today. Various types of information manipulation are often carried out, even by academic people who uphold the value of honesty. This paper aims to provide information to the reader, that librarians have more role in the problem of information manipulation, especially regarding plagiarism that occurs in the academic environment (universities). The author uses the case study method that occurred at UPT. Muhammadiyah Ponorogo University Library. From this paper, it is known that the majority of students choose to consult with librarians to solve their plagiarism problems.
Research on Encrypted Traffic Classification Method Based on Improved Convolutional Neural Network

Network traffic classification is of great significance to the daily management and maintenance of the network. With the rapid development of encryption techniques for network traffic, traditional traffic classification methods have reduced the accuracy due to the low identification rate of encrypted traffic. Aiming at this problem, a deep learning traffic classification method based on improved convolutional neural network is proposed. By optimizing and adjusting the network structure, network parameters, and cost function of the convolutional neural network, the classification accuracy of encrypted traffic is improved. By comparing and analyzing the existing traffic classification method on public data sets, the experimental results show that the proposed method effectively improves the classification accuracy of encrypted traffic by 10%.
Algorithm Implementation Crochemore Perrin On The Dictionary Application Of Latin Terms Flora And Fauna Based On Android

Searching is the process of selecting the information needed from a collection of data that already exists, data search is often also called a tablelook-up or store and retrieval information. Along with the development of technology that is now so very rapid, one of them is the Smartphone application. Smartphone applications that are currently in demand are increasing sharply, that is Android. Even though the presentation is limited to the screen, Smartphones are quite efficient for its users where the mobility is very high and affordable in all circles of society. used is the string search method. String search method is a string search process or often also called string matching. In the string matching process, there is the Crochemore perrin algorithm, which is an algorithm that factoring a pattern into two parts, namely Pattrenkiri and pattern right. This method is perfect for dictionary search applications of Latin terms flora and fauna.
Learning Hiring Preferences - The AI Behind LinkedIn Jobs

LinkedIn’s Recommended Matches delivers candidate recommendations for your open job posting that get more targeted over time based on your feedback. This new algorithm, which is used throughout the Jobs platform, performs nearly 20% better than the previous version in generating recommendations when we simulate our members' past hiring activity. The technique we leverage to train the targeting to get smarter is called which is learning that happens in real time as our members use the product. Based on how you interact with candidates, our algorithm learns your preferences and delivers increasingly relevant candidates across the Jobs product. Interactions with an applicant versus interactions with a recommended match may be fundamentally different, and so we explicitly represent the channel in which the candidate was discovered in our machine learning model. This also gives us the ability to incorporate online learning from user feedback across additional channels outside our Jobs product in the future like Recruiter Search. Feedback about candidates is aggregated in real time and associated with the corresponding hiring project. A hiring project represents an opening to be filled, and may have a job post, search queries, candidate feedback, and other useful details associated with it. The impact of these online learning features is profound. In fact, the online learning features are 7 of the top 10 most important features in the model. When comparing a model with online learning versus a model without online learning, we found that online learning features provide 49.61% lift in NDCG@1 (averaged over all search queries, with each search query generating one candidate recommendation).
A Computational Grammar of Ga

The paper describes aspects of an HPSG style computational grammar of the West African language Ga (a Kwa language spoken in the Accra area of Ghana). As a Volta Basin Kwa language, Ga features many types of multiverb expressions and other particular constructional patterns in the verbal and nominal domain. The paper highlights theoretical and formal features of the grammar motivated by these phenomena, some of them possibly innovative to the formal framework. As a so-called deep grammar of the language, it hosts a rich lexical structure, and we describe ways in which the grammar builds on previously available lexical resources. We outline an environment of current resources in which the grammar is part, and lines of research and development in which it and its environment can be used.
ЗАВДАННЯ СУЧАСНОЇ ОСВІТИ У ПЕРСПЕКТИВІ ТРЕНДІВ ГЛОБАЛЬНОГО РОЗВИТКУ

A successful example of the integration of modern science into the educational process is the activity of the Club of Rome, the materials of each report of which become an important component of the educational “product” of many higher educational institutions, and especially those which are providing adult education.The perception of the ideas of the Club depended largely on their inclusion in the agenda – political, economic, cultural etc. The quality of such perception depends on the level of competence of those who perceive and on whether they evaluate the forecasts of the Club only as information, or take them as a value. The value perception of predictions of social development enables them to form principles of personal behavior and methodology for the perception and transformation of the social and natural environment. The combination of information and value influence on the individual can be done in different ways, but one of the most effective is the educational means of influence.Indirectly the participants in the activities of the Roman Club have become more than one generation of globalized humanity – since 1968, one can count the life of the third generation.
Supporting Information Security Management : Developing a Method for Information Classification

In the highly digitalised world in which we live today, information and information systems have become critical assets to organisations, and hence need to be safeguarded accordingly. In order to i ...
Secondary High School Students’ Perception towards Teacher Response on EFL Writing

This article is a qualitative study conducted to investigate students’ perceptions towards teacher’s response on EFL writing. The data collected from the students’ reflection of 12 students after receiving feedback from the teacher during three drafting times at one of senior high school in Kendari. The instruments of the study are students’ reflection, and observation sheet. The result of the study showed that students interest towards teacher response (feedback) because it has positive affect in learning English especially on EFL Writing.However,teacher responses help them in correcting their errors in writing. Students assume it can help in developing new ideas, identify error words, punctuation and also build new inspiration in writing process. The implies of the study, teacher response in learning English especially writing skill can improve students insight and knowledge to be better than before. Teacher feedback makes easier for students to know their mistakes in writing process. Key words: Error writing, Students’ reflection, Teacher response.
Li Yuan, Tao Wang, Xiaopeng Zhang, Francis EH Tay, Zequn Jie, Wei Liu, Jiashi Feng

Existing data-dependent hashing methods usually learn hash functions from pairwise or triplet data relationships, which only capture the data similarity locally, and often suffer from low learning efficiency and low collision rate. In this work, we propose a new \emph{global} similarity metric, termed as \emph{central similarity}, with which the hash codes of similar data pairs are encouraged to approach a common center and those for dissimilar pairs to converge to different centers, to improve hash learning efficiency and retrieval accuracy. We principally formulate the computation of the proposed central similarity metric by introducing a new concept, i.e., \emph{hash center} that refers to a set of data points scattered in the Hamming space with a sufficient mutual distance between each other. We then provide an efficient method to construct well separated hash centers by leveraging the Hadamard matrix and Bernoulli distributions. Finally, we propose the Central Similarity Quantization (CSQ) that optimizes the central similarity between data points w.r.t. their hash centers instead of optimizing the local similarity. CSQ is generic and applicable to both image and video hashing scenarios. Extensive experiments on large-scale image and video retrieval tasks demonstrate that CSQ can generate cohesive hash codes for similar data pairs and dispersed hash codes for dissimilar pairs, achieving a noticeable boost in retrieval performance, i.e. 3\%-20\% in mAP over the previous state-of-the-arts. The code is at: \url{this https URL}
Economic challenges of cloud computing in Iraqi educational institutions using exploratory analysis

&lt;span&gt;Cloud computing (CC) implementation for educational services is confronting several challenges. Prior research focused on the technological related challenges while few examine the economic challenges. The purpose of this study is to examine the economic challenges for using CC in educational institutions in Iraq. Articles pertaining to the topics were extracted from main databases. Based on the review, the critical challenges were identified. To confirm their relatedness to Iraqi context, a questionnaire related to the challenges was developed. A total of 204 respondents working as IT professional has participated in this study. The findings showed that the challenges mainly related to the infrastructure readiness, internet connection, cost of establishing and managing the CC. The challenges were divided into three phases. The pre-implementation phase includes the challenges of selecting service provider and deployment as well as the readiness of stakeholders, training, and infrastructure readiness. The implementation phase includes the challenges of maintaining the bandwidth, compatibility, legacy system, internet connection, reliability, availability, connectivity, and management. The post-implementation phase includes the challenges of security, privacy, quality of education, switching cost, and lock-in. The most critical challenges in all phases are related to infrastructure readiness, internet connection, switching cost and management of CC. The findings were discussed and limitations of the study as well as the direction for future works were given. &lt;/span&gt;
The Problems of Africa’s Industrialization Substitution Strategy and Reformation Needs

This study showed that industrialisation by substitution of imports has been a failure in Africa and has made industries in this part of the world less competitive on the foreign market. As such, a different industrialisation strategy which in the context of globalisation of economies and the fierce competition of the international market reinforces the competitiveness of African countries. This new strategy was translated amongst others by the appropriation of new technologies, protection of infant industries, cloning of manufactured products imported out of Africa, regional integration and the culture of exporting manufactured products.
The space between us: how designers and the general population see typographic emphasis

The typographic emphasis of headings in a document clarifies the structure of the content for the reader as well as assisting them with locating information.The visual presentation of these headings is important so that they are effective visual markers.The typographic methods used to emphasise these headings can vary greatly and are potentially perceived different by those consuming the document compared to those who are designing it.The research presented in this paper investigates through a paired comparison study whether designers perceive the typographic emphasis methods used for headings in the same way as the general population.While the effectiveness of heading styles is generally agreed between both groups, the greatest discrepancy occurs regarding the use of spacing.Through the comparative study assessing seven methods of typographic emphasis, it was found that designers consider spacing to be more effective for indicating typographic hierarchy than those in the general population.
META-ANALYSIS OF THE EFFECT OF MAKE A MATCH LEARNING MODEL ON PRIMARY SCHOOL STUDENT LEARNING OUTCOMES

This study aims to determine the effect of the Make a Match learning model on learning outcomes of elementary school students. The method used in this research is meta-analysis method. This study is to determine whether the Make a Match learning model can improve student learning outcomes. In the next stage, collect relevant articles to collect data. The data was obtained from online journal searches through Google Scholar, where 10 articles were obtained. The keywords used are "Make a Match learning model" and "learning outcomes". Data were obtained and re-analyzed using quantitative methods. Based on the results of the analysis, there is an effect of the Make a Match learning model on student learning outcomes with an average after being given treatment that is 46.946 with an average before being given treatment that is 35.963. So it can be concluded that there is an effect of the Make a Match learning model on the increase in student learning outcomes, namely 10 . 983.
The Tagged Corpus (SYN2010) as a Help and a Pitfall in the Word-formation Research

Today, language corpora are the primary source of linguisticobservation. The purpose of this paper is to illustrate some ofthe problems associated with word-formation research based uponmorphologically tagged synchronous corpora.
Исследование алгоритма обнаружения детерминированных аномалий на сложных изображениях с помощью дважды стохастической модели

The article proposes an algorithm for detecting deterministic anomalies against the background of satellite images with a complex structure, containing a combination of several natural objects. To describe such images, doubly stochastic models of random fields are proposed, which provide the formation of inhomogeneous images. The effectiveness of the algorithm is estimated by the probability of correct detection under various conditions of the interference. The dependences of the probability of the correct detection on the signal-to-noise ratio at various thresholds are presented. We present the detection efficiency studies on simulated and real images. The results are compared with the algorithm based on autoregressive random fields. We demonstrate that the proposed algorithm provides the efficacy in reducing the signal-to-noise ratio to achieve the given probability of the correct detection. Andriyanov N. A., Gavrilina Yu. N. Investigation of the algorithm for detecting deterministic anomalies in complex structure images using a doubly stochastic model.  Ural Radio Engineering Journal . 2020;4(1):18–32. DOI: 10.15826/urej.2020.4.1.002
Design and Build Information System of the Joper Chicken Plasma Core at PT. Barokah

Breeding joper chickens with a partnership system is a form of business that is currently on the rise, breeding in partnership is a form of cooperation between breeders (plasma) and companies (nucleus). The yields will be divided according to the percentage agreed upon in the contract agreement that has been made between plasma and nucleus. It takes approximately 12 weeks for the farmer to raise the chickens until harvest. During this period, breeders must take care of the chickens maximally so that it is hoped that the harvest will be profitable for both the farmer as the plasma and the company as the nucleus. There needs to be extra careful management in the process of cultivating joper chickens because chicken farming can be said to have a high enough risk. Therefore, this system was built in order to overcome problems such as irregular feeding or vaccines, manual recording of daily chicken development, disease management and lack of insight into diseases that chickens often get, as well as weighing calculations that are still being carried out. Manually. So that by overcoming these problems the crop yields will increase and the level of productivity of chickens is controlled. The tools used in making this system are Visual Basic. Application design method using ProtoTyping method.
PENINGKATAN PENGETAHUAN TENTANG PENTINGNYA UPDATING DATA SINTA MELALUI EDUKASI ONLINE DI LINGKUNGAN UNIVERSITAS

The spread of the COVID-19 is the cause of death with the highest number in the world so that the government enforce work from home rule .The work from home rule causes activities such as teaching and learning, training, and seminar conducted via online education . The purpose of this activity is to educate online about the importance of updating data in sinta. The method of activity is carried out with socialization (lecture) and FGD (Focus Group Discussion). The target of this activity is the campus community consisting of staff-bureaus, lecturers, and the rest of the university staff. The number of participants who participated was 79 people. Most were from the faculty of health sciences (25.3%), law (15.2%), economics and business (13.9%), psychology and engineering (11.4%) . The results of the socialization showed that most participants understood about the importance of updating data in sinta ; knowledge (good) 51.9%. The results of the FGD showed that participants mainly discussed the creating a sinta account (25%), synchronizing data from old inst itution to new institution (25%), consulting services in sinta (37.5%), and classifying expertise or research themes in sinta (12.5%). As many as 100% expressed an understanding about updating data in sinta . This activity increase d knowledge about the importance updating data in sinta by 48.1%. Thus, it is important to carry out an educational activities especially with online methods routinely and periodically in an effort to increase knowledge regarding the conditions of the pandemic. Â  Keywords: Online Education, COVID-19, Knowledge, Sinta
The Effective Guarantee of Comprehensive Reform of Regional Education

Comprehensive reform of regional education is a long-term systematic project that involves many interest groups, has a great social impact and exhibits very distinctive regional and local peculiarities. It is extremely difficult and complex. Therefore, we need to take practical measures to ensure its orderly implementation and find effective solutions to the more profound problems in intraregional education.
Research Guides: Advertising and Public Relations: Websites

Library resources to support research in learning in the area of advertising and public relations. Enter a description for the Citation Help page.
Three-Dimensional Operating Room with Unlimited Perspective

Apart from operating tables and modern surgical instruments, the modern operating rooms are equipped with displays and video surveillance systems. The three-dimensional operating room allows users to watch medics perform surgery from different, individually chosen, points of view. For the first time, it is possible to reproduce/repeat the course of the operations and change the perspective or position, from which it is observed. Here, we proposed a solution based on Microsoft HoloLens and Azure Kinect DK devices as remote support to patient management. The operating room is transferred to the digital form in real-time using Augmented Reality based technologies. Users can move around the digital place like a ghost in real space. The approach proposed allows users to see observe surgery from any point of view they want without disturbing the surgeon’s workflow. They can change their positions, angle, and place of observation. All environmental restrictions disappear. The presented solution gives trainees a convenient opportunity to learn. It may make a significant contribution to improving the surgeon training, patients’ outcomes, and may allow virtual medical consultations during the surgery between specialists without them leaving their workplace.