Reviewerly/exHarmony huggingface dataset:
Access to data for training algorithms in machine learning: copyright law and right-stacking

News services and information gathering services are increasingly relying on automated processes. As information sources are unlimited and often unreliable, it is important from an information security perspective that services using artificial intelligence to process information are able to draw and present reliable conclusions. This Chapter examines if and how exclusive rights in copyright law restrict data access for training algorithms for the purpose of machine learning. Because access to huge amounts of data is necessary to train algorithms to develop high quality artificial intelligence services, the rights of authors to individual works as well as rights in collections of works - database rights and publisher's rights - must be cleared. The Chapter discuss the role of copyright law in striking a balance between right holders and AI developers and how public interests can be included in the balance. The discussion plays into the larger policy debate: whether the role of intellectual property rights is developing from incentive mechanisms to control mechanisms.
A Utilização de Ferramentas Móveis por Enfermeiros para Auditoria em Saúde/ The Use of Mobile Tools by Nurses for Health Auditing

Objective: to seek evidence in the literature on the use of mobile tools that facilitate the practice of auditing medical bills by the auditor nurse.Method: this is an integrative review, which brought the following guiding question: how does the use of mobile tools by nurses for health audit help and ensure efficiency and effectiveness in this task?The search took place in three databases.Results: 06 articles, that addressed the use of mobile technologies in nursing by nurses and that met the objective of the study, were selected.Conclusion: mobile tools are instruments to improve the quality of care provided and the records made by the nursing staff, as well as in hospital management, being, therefore, their use by nurses for health auditing effective and efficient.
Scramsis Game (Syntak Scramble) Innovation Of Basic Programming Educational Games For Students Of Class X Tkj Smk Muhammadiyah 1 Wates

This study aims to: develop a Scramsis game that contains basic programming material for class X TKJ SMK Muhammadiyah 1 Wates and test the quality of the Scramsis game based on the ISO 25010 quality standard. This research is a research and development research using the Waterfall model which includes communication, planning, modeling, construction, and distribution. The functional suitability quality test was carried out by 2 developers, while the usability test was carried out by students of class X TKJ SMK Muhammadiyah 1 Wates. The results of this study are: (1) Game Scramsis has six main menus, namely let's play, how to play, settings, profiles, instructions, and exit. Scramsis has 3 different levels of difficulty.. Game Scramsis got a score of 100% on the functional suitability quality test which means very high quality, 100% on the compatibility quality test which means very high quality. Scramsis' performance efficiency test is seen from CPU and memory usage, the average CPU usage of Scramsis is 2.71%, when compared to the CPU limit set by little eye, which is 15%, this usage is still very safe. Scramsis' performance efficiency test is seen from CPU and memory usage, the average CPU usage of Scramsis is 2.71%, when compared to the CPU limit set by little eye, which is 15%, this usage is still very safe. The use of scramsis memory is 129 MB and does not experience force close. The usability test was carried out on class X TKJ. Scramsis' performance efficiency test is seen from CPU and memory usage, the average CPU usage of Scramsis is 2.71%, when compared to the CPU limit set by little eye, which is 15%, this usage is still very safe. The use of scramsis memory is 129 MB and does not experience force close. The usability test was carried out on class X TKJ SMK Muhammadiyah 1 Wates and got a score of 80.02% which was included in the quality category and the Cronbach alpha reliability value from the usability test questionnaire was 0.828 which means good.
Artificial intelligence and intellectual property rights: the quest or plea for artificial intelligence as a legal subject

Artificial intelligence (AI) can create a vast number of physical and intangible systems even today. Increasingly, tasks and jobs traditionally done by natural persons in various fields will be fulfilled by these non-human entities. In turn, these automated activities have vast financial and legal consequences, which points to the fact that the less meaningful human control is, the greater the need will be to regulate AI entities. In this regard, a key question relates to the legal nature of these non-human actors. By placing our analysis in the specific industry context of entertainment and the media and in relation to the legal framework of IPR, this Chapter investigates the need to regulate AI actors as legal subjects. This encompasses taking a critical look as to the feasibility of recognizing AI entities and systems as legal persons for IPR purposes, as well as the possible need to create a new sui generis legal subjectivity for independently functioning AI entities and systems.
Preface

We present and analyse Las Vegas distributed algorithms which compute a MIS or a maximal matching for anonymous rings. Their bit complexity and time complexity are O(logn) with high probability. These algorithms are optimal modulo a multiplicative constant. Beyond the complexity results, the interest of this work stands in the description and the analysis of these algorithms which may be easily generalised. Furthermore, these results show a separation between the complexity of the MIS problem (and of the maximal matching problem) on the one hand and the colouring problem on the other. Colouring can be computed only in Ω(logn) rounds on rings with high probability, while MIS is shown to have a faster algorithm. This is in contrast to other models, in which MIS is at least as hard as colouring.
Supplemental Material: New constraints on the timing and character of the Laramide Orogeny and associated gold mineralization in SE California, USA

Tables S1–S9 with analytical details and results of all analyses conducted, and Figures S1–12.
Multi-View Subspace Clustering by Combining ℓ2,p-Norm and Multi-Rank Minimization of Tensors

In this article, based on the self-represented multi-view subspace clustering framework, we propose a new clustering model. Based on the assumption that different features can be linearly represented by data mapped to different subspaces, multiview subspace learning methods take advantage of the complementary and consensus informations between various kind of views of the data can boost the clustering performance. We search for the tensor with the lowest rank and then extract the frontal slice of it to establish a well-structured affinity matrix. Based on the tensor singular value decomposition (t-SVD), our low-rank constraint can be achieved. We impose the ℓ2,p-norm to flexibly control the sparsity of the error matrix, making it more robust to noise, which will enhance the robustness of our clustering model. With combining ℓ2,p-norm and tensor multi-rank minimization, the proposed Multi-view Subspace Clustering(MVSC) model can effectively perform clustering with multiple data resources. We test our model on one real-world spoon dataset and several publicly availabe datasets. Extensive evaluation methods have proved that our model is effective and efficient.
Design Build and Analyze of Website Usability of Campus Publishing Agency

Introducing a product certainly requires a medium or intermediary so that the product can be known by the wider community. One of the most frequently used media nowadays is the website or marketing site. The main purpose of this website is to promote products that have been made based on the works of the authors to be better known to the wider community. A website must also be user-friendly, easy to understand, access, remember, and provide useful information to its users. The creation of this website uses the Web Development Life Cycle (WDLC) method, the website will be tested using the usability model which is a qualitative analysis to determine how easy the user is using the interface of an application. The data collection techniques will use the interview technique, with the determination of the sample with purposive sampling technique. The Data obtained later will be analyzed and tested validity with techniques found in qualitative research methods.
“MR Q-Learning” Algorithm for Efficient Hardware Implementations

The maximum value finder block is one of the most critical parts in the hardware implementation of the Q-Learning Reinforcement Learning algorithm. To solve this issue, we propose the MaxReset Q-Learning (MR Q-Learning) algorithm. We replaced the high-dimensional combinational maximum finder tree with an architecture based on a dual port RAM and a pseudo-random number generator used to trigger the algorithm. This approach allows to reduce propagation delay and power dissipation while maintaining the same training results of the original algorithm. The computational precision of MR Q-Learning was tested and compared to Q-Learning in a dynamic environment used as benchmark.
Clustering of Modal Valued Data

Adapted versions of k-means and hierarchical clustering for modal valued data are presented. All symbolic variable values (partitionings) are treated as unordered categories; and represented as empirical probabilities with known totals/sizes. This type of representation allows the adapted algorithms to use totals/sizes (or more generally sums of all category values) as weights. We show that when the (weighted) squared Euclidean dissimilarity measure is applied to the adapted methods, the final cluster representatives are also composed of distributions of variable values in these clusters. The clusters are therefore easily interpretable and can be further quantified by using the cluster specificity index for each symbolic variable to compare cluster representative with the representative of the entire dataset. In addition, characteristic components of each symbolic variable in the cluster can be quantified using the contrast index. The adapted method is applied to the TIMSS data, and the results are interpreted using the newly defined cluster specificity and contrast indices.
Iteration Graph Network

Graph neural networks are widespreadly used in the field of graph data analysis and processing. Recent methods either reduce the spatial receptive field for low algorithm complexity, or greatly lose efficiency in order to realize attention mechanism. To tackle this issue, we propose Iteration Graph Network (IGN), which uses an iterative inversion method to aggregate node feature and the k-localized neighbor information of nodes. In the graph-based semi-supervised node classification task, our method surpasses the state-of-the-art method in the benchmark datasets and experiment conclusion show that our model outperforms graph attention networks (GAT) and is more than 3 times faster than graph attention networks, consumes more than 6 times less memory than GAT. Our code will be make publicly available.
Multi Adaptive Hybrid Networks (MAHNet): Ensemble Learning in Convolutional Neural Network

Convolutional neural networks are very successful in object classification and detection, thanks to constantly evolving neural network architectures. Although these architectures are quite successful, hybrid models can also be a better solution to different problems by combining with different architectures. In this study, it is aimed to create a hybrid model with different architectures. However, module selection is adaptive rather than predetermined. In order to achieve this, the new selection layer is selected from modules of different architectures trained in parallel with the ensemble learning perspective. The coefficient created for each module is used as a boosting ensemble learning. However, unlike boosting, module selection is made according to these weights.
Working with Files and Folders

Being the powerful editor it is, Visual Studio Code provides a convenient way of working with code files and folders containing both loose files and projects. In this chapter you will learn how to work with individual files, with folders containing source code files, and with workspaces. You will also learn about VS Code’s independence from proprietary project systems as well as its built-in support for a few popular project types.
Multi-Class Classification with Asymmetric Error Control for Medical Disease Diagnosis

There is a growing need for asymmetric error control in medical disease diagnosis because the cost of a false negative may greatly exceed the cost of a false positive. This paper aims to extend the asymmetric error control achieved using the Neyman-Pearson (NP) Lemma in binary classification to multiclass classification. The NP oracle inequalities for binary classes are not immediately applicable for the multiclass NP classification, leading to a multi-step procedure to extend the algorithm in the context of multiple classes. Firstly, a hierarchical order of severity for misclassification for each class is maintained and the most critical classes identified. Secondly, the NP methods are applied to classify the most critical class versus the rest, and then the NP methods are applied to the next most severe class in the list versus the rest until a label is assigned. This approach is used to construct a novel tree-based classifier that enables asymmetric error control for multiclass classification and is evaluated on a cardiac arrhythmia dataset, where missing certain types of arrhythmia have more severe consequences than missing others. The results show that we are able to control the number of false negatives for the most critical classes in the multiclass classification problem.
Research on Drill Floor Working Condition Recognition Method Based on Video Understanding

The Drilling Working Condition recognition is a new and challenging research task. We proposed a 3D attentional network based on dual-core modeling (DCM-3D) for recognizing the Drilling Working Condition. Exploring the uniformity and regularity of the drilling working conditions from multiple dimensions, the proposed DCM-3D Net employed the SlowFast framework and designed a 3D attention neural network based on dual-core modeling for effectively spatio-temporal modeling the long rectangular objects. According to the characteristics of the drilling movement and the video continuity, we designed the attention network module and data augmentation module. The experimental results proved that the proposed method effectively improves the performance of the Drilling Working Condition recognition, and surpassed the other state-of-the-art video recognition methods in this task.
An efficient ROI detection algorithm for Bangla text extraction and recognition from natural scene images

This research work plays a significant role in finding information from the scene images to fulfill the demand of real life applications like detection of license plate, navigation of robot and helping the visually impaired persons. Here, a new algorithm has been proposed and applied on the scene images to extract Region of Interest (ROI). All the Bangla words are then separated from a sentence by analyzing and applying the Connected Component (CC) method along with bounding box technology. Another new algorithm has been proposed and applied to apart and bring-out Bangla characters from the Bangla words. This algorithm works by the method of vertical scanning of the images of Bangla words. Finally, the extracted characters are recognized by using the Support Vector Machine (SVM) as a classifier which works with Histogram of Oriented Gradient (HOG) features. There are 500 scene images with variations in colors, writing styles and orientations in our designed database. The proposed algorithm yields the accuracy 92.70% and 93.23% in extraction of ROI and character respectively. In the recognition of Bangla characters (digits, Basic characters, and joined characters), the average accuracy is 99.16%. The recognition accuracy of Bangla characters using Convolutional Neural Network (CNN) is also calculated and the obtained result is 83.52%.
Development of Interactive Learning Multimedia "Mejabando" for Improving Critical and Creative Thinking Skills in Indonesian Language Learning Class V Elementary School

This study aims to produce android-based learning multimedia. The research method used is R&amp;D research with the ADDIE development model (analysis, design, development, implementation, evaluation). The steps in the research include analyzing, designing, developing, implementing, and evaluating. Data collection techniques in this study include interviews, questionnaires, tests, and documentation. The trial was carried out using the One Group Pretest-Posttest Design. The results of this study are (1) the need for multimedia mejabando learning in the high category (2) the validity of the interactive multimedia mejabando from the material expert got a score of 4.18 in the good category and 4.64 from the material expert in the good category (3) multimedia practicality is in the very practical category with a score of 87%, 88% and 89% (4) the effectiveness of interactive multimedia learning mejabando can be seen from the results of the students' pretest and posttest. Critical thinking skills get an N-Gain score of 0.66 in a fairly effective category and N-Gain score for creative thinking skills of 0.57 in a moderately effective category. Based on the results of the research obtained, it can be concluded that the interactive multimedia mejabando learning to improve critical and creative thinking skills in learning Indonesian for fifth-grade elementary school is practical, valid and effective for use in learning. Keywords: Multimedia, critical thinking, creative thinking, Indonesian Language.
Pedagogical Education Modernisation in the University Context

From the essential approach position, the article examines the modern educational organisation formation and functioning as a scientific, educational, training, socio-cultural object that meets the needs of a society; the domestic pedagogical education development priorities and directions are determined; the prospects for the modern pedagogical knowledge formation are identified, this learning is formed under the conditions of the education new paradigm, which characteristic features are digitalisation, network interaction, information transfer distant type, subject's generation of all possible alternatives to reveal the personality individual balance; the dynamics and methodological optics of the modern university research process is analysed; the ways of the pedagogical education available resources rational use are discussed; the methodological practice and the ways of the new practices subsequent multiplication in the university education system, are reflected; the factors, influencing the quality of the modern subject education are established; the degree of the mediatised product influence on the implementation of the contemporary pedagogical university educational strategy is defined; the toolkit of specialist's training and education, demanded by the labor market, is investigated; an approach is implemented, identifying a modern student in his development, which helps to determine the pedagogical substance movement nature, to recreate a holistic picture of the available reserves and means necessary for the personality education at a qualitative level.
Pengembangan Sistem Informasi Pendaftaran Praktek Kerja Lapangan (PKL) dengan Konsep Hierarchical Model View Controller (HMVC)

Registration for Praktek Kerja Lapangan (PKL) in the Administration Business department has not been maximized. Some of the problems that occur include student registration which is still semi-manual so that it prolongs the registration process, one company only have three students for each Study Program so that students have to fight, this makes it difficult for the admin, manual PKL registration makes students have to queue in the administration room. The development of an information system with the HMVC pattern is able to make easier for programmers. Programmer can divide the system into more specific modules so that the execution of applications is more flexible. This research purpose to develop a registration information system for Praktek Kerja Lapangan (PKL) by applying the HMVC (Hierarchical Model View Controller) concept. The test results of the three experts show that all features of the PKL registration information system are running and functioning properly. And then, stress testing with Jmeter also showed satisfactory results, using 42 users / samples the average response time was less than 5 seconds and there were no errors.
Digital Communication across Culture: A Case Study of the Linguistic Features of WhatsApp Communication and Applied Linguistics

Digital Communication across Culture: A Case Study of the Linguistic Features of WhatsApp Communication and Applied Linguistics Abdullah Khuwaileh Abstract The central aim of this study is to measure the level of linguistics in the appliedWhatsApp communication among people including their social and academiclife as the number of people using digital communication including theWhatsApp has remarkably increased worldwide. To ensure reliable data andresults, we collected our data randomly from the society of the North ofJordan, definitely from Jordan University of Science and Technology (hereafterJUST) and the area surrounding the campus (Irbid area). Samples were bothmales and females B.A., B.Sc. and M.A. students (200 respondents forquestionnaires and 10 educationalists and/or fathers for semi-structuredinterviews). Moreover, the researcher monitored Jordanian soft and hard massmedia to collect observations about people reaction towards the WhatsApp.Tabulating and filtering out the responses given in the questionnaires andinterviews revealed that the application of WhatsApp has both semioticnegative and positive effect on people depending on users and their purposes.Whereas a considerable number of people saw the WhatsApp application as asource of serious problems like semiotic human addiction, cheating in variouseducational tests, reducing physical communication and time wasting, etc.,many others found it as a very good means of digital, cheap, fast and clarifiedcommunication which can carry heavy electronic loads like video clipsand images. Our study is concluded with a number of research and practicalrecommendations. Full Text: PDF DOI: 10.15640/ijlc.v8n1a3