Reviewerly/exHarmony huggingface dataset:
AI Patents: A Data Driven Approach

The global technology market exceeds $12 trillion. The market’s fastest growing niche is artificial intelligence (AI). Yet, while the literature on technology patents is theoretically robust - the literature on AI patents is relatively uncharted. As a consequence, lawyers, scholars, and commentators often refer to AI as a black box – arguing not even advanced computer scientists understand how it works. But all AI technology is written with formal logic, mathematics, and computer code. Thus, all AI systems are syntactically describable, repeatable, and explainable. In other words, there is no black box.This Article empirically analyzes the unique intellectual property strategy decisions technology firms face by introducing a dataset including four specific types of machine learning patents: deep learning, reinforcement learning, deep reinforcement learning, and natural language processing. Dataset charts, models, and graphs, provide insight into market alcoves, while analysis of each machine learning technology shines a light through the “black box.” Further, patent claims analysis reveals significant overlap in patented AI technologies. In sum, this Article draws on a growing body of informatics, intellectual property, and technology scholarship to provide novel patent analysis and critique.
True Vertical and Orthogonal OBN Sensing with 3C MEMS Sensors

Summary OBN projects are taking an increasing market share over towed streamer surveys. Despite significantly higher costs of operation, OBN enable flexible layout strategies (e.g., for the recording of long multi-azimuth offsets), seismic wavefield recording with high signal-to-noise ratio (stationary sensors located in a low-noise environment), broadband signal recording (exceptional deghosting with receiver ghost well separated from the primary signal, in combination with dual pressure and velocity sensing), the recording of PS waves and a better repeatability for 4D surveys. Until now all OBN available on the seismic market have been equipped with 3C omni-tilt 15Hz geophones however a recently released node offers 3C MEMS sensors as an alternative. MEMS are renowned for their ability to record seismic signal with true amplitudes and phases, from DC to 800 Hz, contrary to geophones whose sensing fidelity varies with manufacturing tolerances, ageing and temperature. In addition, the third generation of MEMS ( Lainé 2014 , Fougerat 2018 ) has overcome the low-frequency limitations associated with previous generations. A recent field test could demonstrate that contrary to the case with 3C geophones, 3C MEMS have in addition the ability to measure particle motion along truly vertical and horizontal axes, which is a major benefit for OBN applications.
LibGuides: Academic Study Skills Offer: Level 3 and Access sessions

A short guide to our in-class support sessions An overview of available Study Skills sessions for L3 FE classes
Analysis Framing of the Presidential Election News in LensaIndonesia.com Online Media

Ini merupakan hasil cek plagiasi dari artikel berjudul Analysis Framing of the Presidential Election News in LensaIndonesia.com Online Media yang ditulis oleh Vidya Mandarani, M.Hum, dipublikasikan di konferensi Proceedings of International Conference on Advances in Education, Humanities, and Language (ICEL) “Mainstreaming the Influences on Higher Order of Thinking Skills in Humanities, Education, and Language in Industrial Revolution 4.0” di URL : http://icel.fib.ub.ac.id/wp-content/uploads/2019/08/PROSIDING-ICEL-2019-LayoutFinal.pdf
Trends of Manifestation of the Inclusive School Culture in the Context of Music Education

"The article presents the analysis and scientific assessment of trends of the inclusive school culture, manifesting themselves in the context of music education. It is maintained that school culture grounded on the philosophy of inclusive education and enriched with advanced educational processes, in this case, with artistic/musical activities, not only marks the school’s uniqueness but also highlights the importance of the educational process, unites and empowers its participants to work together naturally to achieve a common goal. Building the inclusive school culture, music education correlates with all of its main features manifesting themselves in reality: the collaboration of participants of the educational process, dissemination of best practice, favourable microclimate ensuring the manifestation of a successful situation not only in the educational process but also in concert activities, and the like. Music activity grounded on the philosophy of inclusive education becomes an aspiration building the inclusive school culture, which undoubtedly helps to create the society grounded on tolerance of differences, which seeks to envisage every learner’s needs and possibilities. Keywords: school culture, inclusive school, music education."
The Effects of Online and Offline Customer Experiences on Customer Loyalty in Chinese Fresh E-commerce

With the gradual upgrade of fresh food consumption in China, the integration of online platforms and retail entities has brought more convenient and diverse fresh food consumption experiences to cu ...
Efektivitas Portal Akademik Sebagai Sarana Penyampaian Informasi Akademik Bagi Mahasiswa STIA NUSA

Iqbal Hanafi’s (1610078201045) study of the Academic Portal’s Effectiveness As a Medium of Academic Information for Students of STIA NUSA. The purpose of this study is to Know the extent of the Effectiveness of the Academic Portal STIA NUSA as a Means of Delivering Information to Students; to Know of the Obstacle that Limit the Spread of Information Trough the Official Stia Nusa Portal; and to Know the Constraint on the Part of the Academic Portal Authority STIA NUSA in Providing an Up to Date Information. The study employs a descriptive analitycal qualitative research approach. Data collection takes place through interviews, observation and documentation. Research indicates that the Academic Portal of STIA NUSA has not been efective as a means of communicating information for students is proven with a students’s tendency to search for information related information that exists on STIA NUSA by coming directly to the campus or looking separately from the portal by examining the college’s social media. The utilization of features on the portal is less due to the lack of socialization and the lack of administrator’s strength in the academic ward. Lack of hardware of owned servers, lack of campus expertise and control over the content of academic portals, and a frequent link to tissue interference.
$α$-Information-theoretic Privacy Watchdog and Optimal Privatization Scheme

This paper proposes an $\alpha$-lift measure for data privacy and determines the optimal privatization scheme that minimizes the $\alpha$-lift in the watchdog method. To release data $X$ that is correlated with sensitive information $S$, the ratio $l(s,x) = \frac{p(s|x)}{p(s)} $ denotes the `lift' of the posterior belief on $S$ and quantifies data privacy. The $\alpha$-lift is proposed as the $L_\alpha$-norm of the lift: $\ell_{\alpha}(x) = \| (\cdot,x) \|_{\alpha} = (E[l(S,x)^\alpha])^{1/\alpha}$. This is a tunable measure: When $\alpha < \infty$, each lift is weighted by its likelihood of appearing in the dataset (w.r.t. the marginal probability $p(s)$); For $\alpha = \infty$, $\alpha$-lift reduces to the existing maximum lift. To generate the sanitized data $Y$, we adopt the privacy watchdog method using $\alpha$-lift: Obtain $\mathcal{X}_{\epsilon}$ containing all $x$'s such that $\ell_{\alpha}(x) > e^{\epsilon}$; Apply the randomization $r(y|x)$ to all $x \in \mathcal{X}_{\epsilon}$, while all other $x \in \mathcal{X} \setminus \mathcal{X}_{\epsilon}$ are published directly. For the resulting $\alpha$-lift $\ell_{\alpha}(y)$, it is shown that the Sibson mutual information $I_{\alpha}^{S}(S;Y)$ is proportional to $E[ \ell_{\alpha}(y)]$. We further define a stronger measure $\bar{I}_{\alpha}^{S}(S;Y)$ using the worst-case $\alpha$-lift: $\max_{y} \ell_{\alpha}(y)$. We prove that the optimal randomization $r^*(y|x)$ that minimizes both $I_{\alpha}^{S}(S;Y)$ and $\bar{I}_{\alpha}^{S}(S;Y)$ is $X$-invariant, i.e., $r^*(y|x) = R(y), \forall x\in \mathcal{X}_{\epsilon}$ for any probability distribution $R$ over $y \in \mathcal{X}_{\epsilon}$. Numerical experiments show that $\alpha$-lift can provide flexibility in the privacy-utility tradeoff.
A Comparison of Approaches to Document-level Machine Translation

Document-level machine translation conditions on surrounding sentences to produce coherent translations. There has been much recent work in this area with the introduction of custom model architectures and decoding algorithms. This paper presents a systematic comparison of selected approaches from the literature on two benchmarks for which document-level phenomena evaluation suites exist. We find that a simple method based purely on back-translating monolingual document-level data performs as well as much more elaborate alternatives, both in terms of document-level metrics as well as human evaluation.
PELATIHAN PEMBUATAN NOMOR POKOK WAJIB PAJAK SECARA ONLINE MELALUI APLIKASI ZOOM BAGI MAHASISWA KOTA BATAM

The purpose of this community service program is to educate the students in Batam that still unfamiliar with NPWP and even do not have NPWP to get NPWP online. The methods used in this activity are Education, training, and consultancy online through Zoom Application for one semester. The results of implementation showed that students become educated and understand the role of NPWP in daily life and how to register it online and 10 students successfully registered and got NPWP.
Re-Engineering Justice? Robot Judges, Computerised Courts and (Semi) Automated Legal Decision-Making

This paper takes a sceptical look at the possibility of advanced computer technology replacing judges. Looking first at the example of alternative dispute resolution where considerable progress has been made in developing tools to assist parties to come to agreement, attention then shifts to evaluating a number of other algorithmic instruments in a criminal justice context. The possibility of human judges being fully replaced within the courtroom strictu sensu is examined, and the various elements of the judicial role that need to be reproduced are considered. Drawing upon understandings of the legal process as an essentially socially determined activity, the paper sounds a note of caution about the capacity of algorithmic approaches to ever fully penetrate this socio-legal milieu and reproduce the activity of judging, properly understood. Finally the possibilities and dangers of semi-automated justice are reviewed. The risks of seeing this approach as avoiding the recognised problems of fully automated decision-making are highlighted, and attention is directed towards the problems that remain when an algorithmic frame of reference is admitted into the human process of judging.
A Technical Report for Light-Edge: A Lightweight Authentication Protocol for IoT Devices in an Edge-Cloud Environment

Selected procedures in [1] and additional simulation results are presented in detail in this report. We first present the IoT device registration in Section I, and we provide the details of fuzzy-based trust computation in Section II. In the end, we show some additional simulation results for formal validation of the Light-Edge under On-the-Fly Model Checker (OFMC) and Constraint-Logic-based ATtack SEarcher (CLAtse) tools in Section III. See the original paper [1] for more detail.
Some Aspects of Localization of Pyrite Mineralization Within the Subarctic Region

Summary Considered theoretical and practical aspects of disposal of pyrite mineralization within Ural North. Disclosed leading geodynamic processes responsible for the formation of massive sulfide mineralization which are convergent and divergent conditions producing undifferentiated and differentiated (contrasting and continuous) volcanic formation. Compact in tabular form practiced ranking ore objects, the characteristic of near ore metasomatic rocks, ores on the main (Cu, Zn, Pb) elements including noble (Au, Ag, Pt, Pd) metals. Developed regional (structural-tectonic, formational) and local (structural and morphological facial, petrophysical, petro-geochemical) paleovolcanic criteria for a positive predictive assessment pyrite family, within which four ore-formational type isolated (Cyprus, the Urals, orealtay, Filizchay) established their spatial position and age. The presence of two metallogenic epochs of massive sulfide formed on North Urals in relation to the total of the geodynamic evolution of the territory of several different from the Middle and South Urals
Diversity and its role in computing resources for further reflection

Last July, members of Computing for the Social Good in Education (CSGEd) community issued the following statement and associated resources.
A Multi-Scale Conditional Deep Model for Tumor Cell Ratio Counting

We propose a method to accurately obtain the ratio of tumor cells over an entire histological slide. We use deep fully convolutional neural network models trained to detect and classify cells on images of H&E-stained tissue sections. Pathologists' labels consisting of exhaustive nuclei locations and tumor regions were used to trained the model in a supervised fashion. We show that combining two models, each working at a different magnification allows the system to capture both cell-level details and surrounding context to enable successful detection and classification of cells as either tumor-cell or normal-cell. Indeed, by conditioning the classification of a single cell on a multi-scale context information, our models mimic the process used by pathologists who assess cell neoplasticity and tumor extent at different microscope magnifications. The ratio of tumor cells can then be readily obtained by counting the number of cells in each class. To analyze an entire slide, we split it into multiple tiles that can be processed in parallel. The overall tumor cell ratio can then be aggregated. We perform experiments on a dataset of 100 slides with lung tumor specimens from both resection and tissue micro-array (TMA). We train fully-convolutional models using heavy data augmentation and batch normalization. On an unseen test set, we obtain an average mean absolute error on predicting the tumor cell ratio of less than 6%, which is significantly better than the human average of 20% and is key in properly selecting tissue samples for recent genetic panel tests geared at prescribing targeted cancer drugs. We perform ablation studies to show the importance of training two models at different magnifications and to justify the choice of some parameters, such as the size of the receptive field.
Performance Analysis and Improvement of Parallel Differential Evolution

Differential evolution (DE) is an effective global evolutionary optimization algorithm using to solve global optimization problems mainly in a continuous domain. In this field, researchers pay more attention to improving the capability of DE to find better global solutions, however, the computational performance of DE is also a very interesting aspect especially when the problem scale is quite large. Firstly, this paper analyzes the design of parallel computation of DE which can easily be executed in Math Kernel Library (MKL) and Compute Unified Device Architecture (CUDA). Then the essence of the exponential crossover operator is described and we point out that it cannot be used for better parallel computation. Later, we propose a new exponential crossover operator (NEC) that can be executed parallelly with MKL/CUDA. Next, the extended experiments show that the new crossover operator can speed up DE greatly. In the end, we test the new parallel DE structure, illustrating that the former is much faster.
Automatic retrieval of updated information related to COVID-19 from web portals

In the world of social media, we are subjected to a constant overload of information Of all the information we get, not everything is correct It is advisable to rely on only reliable sources Even if we stick to only reliable sources, we are unable to understand or make head or tail of all the information we get Data about the number of people infected, the number of active cases and the number of people dead vary from one source to another People usually use up a lot of effort and time to navigate through different websites to get better and accurate results However, it takes lots of time and still leaves people skeptical This study is based on web-scraping & web-crawlingapproach to get better and accurate results from six COVID-19 data web sources The scraping script is programmed with Python library & crawlers operate with HTML tags while application architecture is programmed using Cascading style sheet(CSS) &Hypertext markup language(HTML) The scraped data is stored in a PostgreSQL database on Heroku server and the processed data is provided on the dashboard © 2020 Ubiquity Press All rights reserved
More Investment in Research and Development for Better Education in the Future?

The question in this paper is whether R\&D efforts affect education performance in small classes. Merging two datasets collected from the PISA studies and the World Development Indicators and using Learning Bayesian Networks, we prove the existence of a statistical causal relationship between investment in R\&D of a country and its education performance (PISA scores). We also prove that the effect of R\&D on Education is long term as a country has to invest in R&D at least 10 years before beginning to improve the level of young pupils.
Analysis of Real-time Blockchain Considering Service Level Agreement (SLA)

The Blockchain technologies enable decentralized networking consisting of large number of nodes.To determine the shared states and failures of all nodes in a fully distributed peerto-peer system, the appropriate consensus algorithm needs to be selected for each Internet of Things system.In this paper, a novel hierarchical voting-based byzantine fault tolerance (HBFT) consensus algorithm is proposed.The proposed HBFT algorithm utilizes a typical PBFT algorithm hierarchically to guarantee low latency.The message complexity of HBFT shows that our proposed algorithm has better scalability.We also mathematically calculate the optimal number of groups based on the total number of nodes to determine the ratio of allowable faulty nodes per group.In addition, we analyze the reliability of byzantine fault tolerance to compare the reliability of group case with the reliability of non-group case.Finally, we introduce the methods of real-time Blockchain considering the service level agreement (SLA).The real-time processing performance of transactions is analyzed for the service level agreement (SLA).
ANALISA PEMBELAJARAN MATA KULIAH AKUNTANSI MENGGUNAKAN TEKNOLOGI INFORMASI DENGAN PENDEKATAN VISUAL LEARNING PADA MAHASISWA AKUNTANSI DI PERGURUAN TINGGI DI KOTA PALEMBANG

The development of high information technology has an impact on the learning process carried out by lecturers in the classroom. The impact of this technology is the creation of lecture material in a visual form both in the form of pictures and videos that are able to provide an overview of the field of science being studied so that students become more interested in the field of science they are learning. This Research is Experimental Research where the accounting student get pre-test and post-test after they get visual learning method. The population in this study is all accounting student at the University at Palembang City. Samples were taken using a purposive random sampling technique. Data was collected using a test result annd questionnaire. Data were analyzed by Paired Sample T-Test. the results of the study showed that there were differences between the learning outcomes of conventional methods and learning using visual learning methods
Elementary EFL teachersâ€™ perceptions on code-switching in primary learning contexts

In this 21st century teaching and learning, there is an intense debate involving language experts whether code-switching should be integrated into EFL learning contexts or not. The supporters of the L2 believed that intense training in the target language will enable EFL learners to be more proficient target language users. While the L1 experts allowed EFL teachers to apply their mother tongue while delivering the teaching-learning materials in order to deliver their teaching-learning instructions clearly for the learners. In line with this contradictory paradigm, EFL teachers need to implement the first language more judiciously in order to preserve learnersâ€™ first language and acquire their target language competencies fully. This study attempted to discover Elementary EFL teachersâ€™ perceptions of the use of code-switching in primary learning contexts. This study utilized narrative inquiry utilizing one research instrument, open-ended interview questions to discover Elementary EFL teachersâ€™ perceptions regarding the utilization of code-switching in primary learning contexts. The participants involving in this study were EFL teachers working in Demangan Baru 1 Elementary School, Yogyakarta. Findings from this study revealed that code-switching did not only help EFL teachers to deliver particular learning materials clearly but also promote greater EFL learning enjoyment for the students.
중국에서의 한국어 발음교육 연구 현황 및 과제

In the new era, along with the belt and road initiative is being promoted, China has put forward higher requirements for minority languages education. In the development of Korean Education for more than 70 years, the study of pronunciation education is still relatively weak compared with grammar and vocabulary. In order to grasp the current situation of Korean pronunciation education as a whole and promote the development of this field systematically, it is necessary to study the history of this field. Based on the volume by volume search of specific journals and CNKI, 85 studies on Korean pronunciation education were selected as the analysis objects. These studies are classified and analyzed according to the standards of publication year, form, theme content, etc., and the theme content is further analyzed according to the nature and objective, content, method, evaluation of the researches. On this basis, the prospect of Korean pronunciation education research in the future is put forward. (Communication University of China)
Representations: New approaches to old problems

Modem cognitive science is built on a foundation of representation. The classical view in cognitive science is that representations consist of abstract symbols that cut across modalities. This view takes the data structures of a computer as a model for cognitive representations. The attacks on the standard view of representation typically begin with a core example that highlights an important problem with representation. From there, an argument is developed that cognitive science should dispense with the classical model of representation in favor of the approach that handles the example presented. In this symposium, we bring together researchers from different perspectives with the goal of having them talk explicitly about how to create a broader theory of representation. The symposium begins with an introduction presented by Arthur Markman, who will discuss the importance of having multiple approaches to representation, and will give an overview of the talks to be presented.