Reviewerly/exHarmony huggingface dataset:
Perencanaan Knowledge Management System Untuk Tata Kelola Perguruan Tinggi

&#x0D; Abstract— A variety of knowledge, especially for universities in making standards, is one of the important things to be managed and documented. The standard drafting process is carried out by the drafting team in holding meetings and meetings directly. Constraints arise when in the drafting process, the drafting team is difficult to determine the time of meeting the standard discussion directly due to busyness and work constraints. In addition, the unavailability of online media repositories for the PPEPP process is another obstacle because the standard documents that have been discussed are only printed and stored as campus files. This storage process is vulnerable to damage, loss, and sometimes it is difficult to do a search if it is merged with other documents. STMIK Multicom management system is not yet available that can accommodate these knowledge. Thus, to ensure the flexibility and changes of STMIK Multicom to keep up with technological developments, a system that can accommodate individual and organizational knowledge in one portal is needed so that the sharing process becomes easier. Through a systematic Knowledge Management System application development plan, the results of system testing conducted on respondents as system users obtained results of 81.16% as the value of benefits for the evaluation of KMS application planning.
Early SNS-based monitoring system for the COVID-19 outbreak in Japan: a population-level observational study

Background The World Health Organization declared the novel coronavirus outbreak (COVID-19) to be a pandemic on March 11, 2020. Large-scale monitoring for capturing the current epidemiological situation of COVID-19 in Japan would improve preparation for and prevention of a massive outbreak. Methods A chatbot-based healthcare system named COOPERA (COvid-19: Operation for Personalized Empowerment to Render smart prevention And care seeking) was developed using the LINE app to evaluate the current Japanese epidemiological situation. LINE users could participate in the system either though a QR code page in the prefectures' websites or a banner at the top of the LINE app screen. COOPERA asked participants questions regarding personal information, preventive actions, and non-specific symptoms related to COVID-19 and their duration. We calculated daily cross correlation functions between the reported number of infected cases confirmed using polymerase chain reaction and the symptom-positive group captured by COOPERA. Results We analyzed 206,218 participants from three prefectures reported between March 5 and 30, 2020. The mean age of participants was 44.2 (standard deviation, 13.2) years. No symptoms were reported by 96.93% of participants, but there was a significantly positive correlation between the reported number of COVID-19 cases and self-reported fevers, suggesting that massive monitoring of fever might help to estimate the scale of the COVID-19 epidemic in real time. Conclusions COOPERA is the first real-time system being used to monitor trends in COVID-19 in Japan and provides useful insights to assist political decisions to tackle the epidemic.
A study: Artificial Neural Networks and its Applications

This paper mainly focuses on the Artificial Neural Networks and its associated application areas. In this paper, prediction and detection of human lung cancer using the concepts of Neural Networks has been discussed. Cancer (Lung cancer) is the leading cause of death in India and other countries as well. The early detection on this dangerous is very important. The prediction and the detection of lung cancer at early stages are being determined by using the concepts of image processing with suitable artificial neural networks models. Artificial Neural Networks has a significant role in the field of medicine. Nowadays, most of diseases are being cured with the help of artificial intelligence and the world is witnessing a revolutionizing era.How to cite this article:Jigyasu D, Ganaie RA. A Study: Artificial Neural Networks and its Applications. J Adv Res Appl Arti Intel Neural Netw 2020; 4(1): 7-9.
A Study on the Value of New Generation Employee Help Scheme in Industrial Organization

The employee help program of EAP (employee assistance program) is a practical and technical system of management psychology which studies the relationship management between the organization and the staff, explores the traditional interaction mode of changing the relationship between the organization and the staff, removes the unfavorable factors that affect the employee's work performance through professional methods, (and finally realizes the goal of harmony and win-win for the service content.The new generation employee help program) is a scientific intelligent management ecosystem based on EAP theory and technology.Through a comprehensive discussion on the background, theoretical exploration, function interpretation, model combing, practice summary and future trend analysis of the new generation employee help plan, the paper clarifies the positive effect of the new generation employee help plan on satisfying the organization and individual's establishment of living ecosystem in the present era.At the same time, it clarifies that the new generation employee help plan is a pioneering and innovative exploration of the theories and techniques of psychology and management, and provides a new way to promote the interdisciplinary integration of psychology, management and economics.
Developing a teaching supplementary worksheet for Morphology Class

Morphology is one of the classes that should be joined by English department students. However, the conventional way to measure the students’ understanding seems unsuccessful. A lecturer of morphology class claimed that written exam in every material given in the classroom was less successful and students tend to be extremely bored when they faced the exam. Based on this phenomenon, the researcher and the lecturer came to the idea that students need to have a new method to measure their understanding. In addition, game is used because it is believed that game is an interesting tool to make students more excited so that they will give much attention on the exam. Research and Development design was used to produce the worksheet product. To finish this product, researcher adopted some steps invented by Borg and Gall which covered need analysis, product development, expert validation, revision, try out and revision. There are 11 games compiled in this worksheet product. Each game provides instructions to play the game and material needed. As the result, students stated that this method, using games, met their need in morphology class. DOI: 10.26905/enjourme.v4i2.4148
One word at a time: adversarial attacks on retrieval models

Adversarial examples, generated by applying small perturbations to input features, are widely used to fool classifiers and measure their robustness to noisy inputs. However, little work has been done to evaluate the robustness of ranking models through adversarial examples. In this work, we present a systematic approach of leveraging adversarial examples to measure the robustness of popular ranking models. We explore a simple method to generate adversarial examples that forces a ranker to incorrectly rank the documents. Using this approach, we analyze the robustness of various ranking models and the quality of perturbations generated by the adversarial attacker across two datasets. Our findings suggest that with very few token changes (1-3), the attacker can yield semantically similar perturbed documents that can fool different rankers into changing a document's score, lowering its rank by several positions.
Análise da aplicação da metodologia SCRUM por uma empresa de consultoria em um projeto de desenvolvimento de software: um estudo de caso

With the growing innovation in software development, many companies find themselves needing to deliver more sophisticated products with shorter lead times. The present work aims to present the agile Software development methodologies, more specifically the Scrum methodology, and to make a comparison between the Scrum framework application model and the model followed by the consultancy company studied, in one of its external projects. The methodology used is a bibliographic research together with a case study. The results show that the method used in the project of the application of the Scrum methodology differs from the theoretical framework, in a way that distances itself from agile principles, increases team stress and interferes with Software development efficiency. Thus, the company should invest more in employee training and seek standardization in applying the Scrum methodology in order to increase the efficiency of future projects.
Learning and Sampling of Atomic Interventions from Observations

We study the problem of efficiently estimating the effect of an intervention on a single variable (atomic interventions) using observational samples in a causal Bayesian network. Our goal is to give algorithms that are efficient in both time and sample complexity in a non-parametric setting. Tian and Pearl (AAAI `02) have exactly characterized the class of causal graphs for which causal effects of atomic interventions can be identified from observational data. We make their result quantitative. Suppose P is a causal model on a set $\vec{V}$ of n observable variables with respect to a given causal graph G with observable distribution $P$. Let $P_x$ denote the interventional distribution over the observables with respect to an intervention of a designated variable X with x. Assuming that $G$ has bounded in-degree, bounded c-components ($k$), and that the observational distribution is identifiable and satisfies certain strong positivity condition, we give an algorithm that takes $m=\tilde{O}(n\epsilon^{-2})$ samples from $P$ and $O(mn)$ time, and outputs with high probability a description of a distribution $\hat{P}$ such that $d_{\mathrm{TV}}(P_x, \hat{P}) \leq \epsilon$, and: 1. [Evaluation] the description can return in $O(n)$ time the probability $\hat{P}(\vec{v})$ for any assignment $\vec{v}$ to $\vec{V}$ 2. [Generation] the description can return an iid sample from $\hat{P}$ in $O(n)$ time. We also show lower bounds for the sample complexity showing that our sample complexity has an optimal dependence on the parameters $n$ and $\epsilon$, as well as if $k=1$ on the strong positivity parameter.
Deep Multi Depth Panoramas for View Synthesis

We propose a learning-based approach for novel view synthesis for multi-camera 360$^{\circ}$ panorama capture rigs. Previous work constructs RGBD panoramas from such data, allowing for view synthesis with small amounts of translation, but cannot handle the disocclusions and view-dependent effects that are caused by large translations. To address this issue, we present a novel scene representation - Multi Depth Panorama (MDP) - that consists of multiple RGBD$\alpha$ panoramas that represent both scene geometry and appearance. We demonstrate a deep neural network-based method to reconstruct MDPs from multi-camera 360$^{\circ}$ images. MDPs are more compact than previous 3D scene representations and enable high-quality, efficient new view rendering. We demonstrate this via experiments on both synthetic and real data and comparisons with previous state-of-the-art methods spanning both learning-based approaches and classical RGBD-based methods.
Guides: Georgetown University Seismological Observatory: Welcome

This guide identifies and provides an overview of resources available in the University Archives which are useful for research into the Georgetown University Seismological Observatory Introduction, overview and brief history of the Seismological Observatory
Quantum circuit to estimate pi using quantum amplitude estimation

This study presents a quantum circuit for estimating the pi value using arithmetic circuits and by quantum amplitude estimation. We review two types of quantum multipliers and propose quantum squaring circuits based on the multiplier as basic arithmetic circuits required for performing quantum computations. The squarer realized by a quantum adder with the gate size of $ O(n) $ requires $ O(n^2) $ gates and at least one ancillary qubits, while that realized by using quantum Fourier transform (QFT) requires $ O(n^3) $ gates without ancillary qubit. The proposed quantum circuit to estimate pi is based on the Monte Carlo method, quantum amplitude estimation, and quantum squarer. By applying the quantum squarer using QFT, the circuit was implemented in $ 4n + 1 $ qubits at $ 2^{2n} $ sampling. The proposed method was demonstrated using a quantum computer simulator with $ n $ being varied from 2 to 6, and the obtained result was compared with the one obtained by performing a classical calculation.
Wearing data: intentions and tensions of art and design in performance using wearables

Wearable technologies have evolved over the last few decades, with 2014 known as “Year of Wearables” in Forbes and other media outlets. Wareable online magazine stated in 2015 that 84 million wearable devices were sold that year, and by 2019 that figure would be 245 million wearable fitness bracelets and other devices. However, a recent report from Statisitca, an online business data analysis platform, suggests that the number is actually closer to three times that amount, roughly 742 million. Such reports show how the industry has grown especially in the last five to ten years. Many tech companies and start-ups have been vying to make the next great wearable device or “killer app” for body-data tracking. Physiological, body-based, sensor devices, and electronic technologies have become cable-free, WiFi-enabled, smaller, more powerful, and sewable, using smart or electronic textiles, conductive fibres and other smart materials. Hardware is increasingly smaller, less visible, and more widely connected; data is more seamlessly and ubiquitously harvested. There has been concurrently rapid and extensive explosion in the development of electronic materials, conductive inks and threads, and new smart materials, fabrics, and textiles for use in various fashion, sports, fitness, medical, military, and governmental projects, as well as for artistic and performance projects, such as those by artists like Kasia Molga’s Human Sensor project for the Invisible Dust organisation. In this chapter I provide an overview of the complex concerns around wearables that draw on datafication and privacy such as using people’s physiological data to sell to health insurance companies to make money off our body data. I begin by discussing the politics of datafication and privacy. I then move on to focus on art, performance and design with wearables and e-textiles, giving examples of my own collaborative wearable performance work and research, to reflect upon some of the novel and productive ways we might think about wearables for future directions in the design of wearables and in the marketplace.
Contraction and Fusion

The purpose of this paper is to explore similarities and differences between contraction and fusion, and to propose a unified approach that contraction is integrated into fusion. Words are generated by way of expansion and reduction. In the expansion method, words are lengthened by addition; in the reduction method, they are shortened by deletion or fusion. Compared to the expansion method, the reduction method does not take place in a regular and predictable manner, and it is not general or universal with respect to word formation but it often appears in the process of word formation. The shortening method includes contraction, fusion, clipping, blending, and acronym. Among them, contraction and fusion appear in many languages, and they show a common merging process. In English contraction, two forms are united into one form; in Korean fusion, a remaining part after a partial or whole deletion is merged into a preceding form. Since contraction and fusion show similar properties with respect to linguistic phenomena, contraction can be integrated into fusion.
Aalto's End-to-End DNN systems for the INTERSPEECH 2020 Computational Paralinguistics Challenge

End-to-end neural network models (E2E) have shown significant performance benefits on different INTERSPEECH ComParE tasks. Prior work has applied either a single instance of an E2E model for a task or the same E2E architecture for different tasks. However, applying a single model is unstable or using the same architecture under-utilizes task-specific information. On ComParE 2020 tasks, we investigate applying an ensemble of E2E models for robust performance and developing task-specific modifications for each task. ComParE 2020 introduces three sub-challenges: the breathing sub-challenge to predict the output of a respiratory belt worn by a patient while speaking, the elderly sub-challenge to estimate the elderly speaker's arousal and valence levels and the mask sub-challenge to classify if the speaker is wearing a mask or not. On each of these tasks, an ensemble outperforms the single E2E model. On the breathing sub-challenge, we study the impact of multi-loss strategies on task performance. On the elderly sub-challenge, predicting the valence and arousal levels prompts us to investigate multi-task training and implement data sampling strategies to handle class imbalance. On the mask sub-challenge, using an E2E system without feature engineering is competitive to feature-engineered baselines and provides substantial gains when combined with feature-engineered baselines.
Documentary monument collection in scientific libraries: Expanding and limiting innovations

Relevant issues of building the collections of documentary monuments in libraries are discussed: principal identification of monuments within the context of functional converging of modern libraries, archives and museums; traditional and innovative approaches to collection structuring, populating, expanding; specific character of museum and archival collections of this type. The author provides multiple examples of traditional archival and museum items included into science library collections provided that they legitimately belong to certain documentary monument type or in case they appear to comprise a well-defined documentary component. The author proves that these documentary monuments non-characteristic for library collections are nevertheless principal for scientific libraries though they may not dominate: the core collections of universal or specialized scientific libraries are made of printed books, other publications, unique and rare valuable publications and items. The current tasks of optimization and updating of documentary monument collections in scientific libraries call for creative non-standard solutions aimed at expansion and modernization of these collections taking into account increased typological variability, i. e. new types and groups of documentary monuments, including valuable digital documents, to be acquired. Innovative approaches have to be based on theoretical, methodological and specialized foundation of expertise, selection, description, preservation activities and revealing new, non-typical collections, as well as on inclusion corresponding disciplines into the librarians’ advanced training curricula. The author emphasizes, however, that modernization does not imply depreciating traditional forms of dealing with the monuments which is the classic of library theory and practice.
Instruments for studying and assessing publication activities at higher schools of culture and arts. (Сase study of Chelyabinsk State Institute of Culture)

The research infrastructure of Chelyabinsk State Institute of Culture and its key research vectors are discussed. The bibliometric analysis of the faculty for the year 2018 is carried out based on the statistical indicators of Russian Science Citation Index, Web of Science and Scopus. The authors emphasize that studying the faculty’s publication activity contributes to the successful development of the Institute’s research infrastructure. With the faculty publication activity data, the university administrations are able to keep track of concepts development, publication types, publication intervals, publications in priority vectors in science, technology and engineering in Russia, etc. The authors also emphasize that authors and publications competitiveness have to be increased, and faculties have to be motivated to publish their research findings in leading academic periodicals. The authors also focus on the role of academic libraries in promoting and increasing publication activity, transforming information services and bibliographic activities. They conclude that universities’ academic libraries today are becoming the innovation sites supporting education and learning processes through their reference and bibliographic services. The obtained data will make the foundation for updating research and creative focuses of university’s chairs and departments.
Summary of PAKDD CUP 2020: From Organizers’ Perspective

PAKDD2020 Alibaba AI Ops Competition is jointly organized by PAKDD2020, Alibaba Cloud, and Alibaba Tianchi platform. The task of the competition is to predict disk failures in large-scale cloud computing environments. We provide SMART (Self-Monitoring, Analysis and Reporting Technology) logs on a daily basis in the production environments without any preprocessing except anonymization. The SMART logs pose great challenges for analysis and disk failure prediction in real production environments, such as data noises and the extreme data imbalance property. In this paper, we first describe the competition task, practical challenges, and evaluation metrics. We then present the statistical results of the competition and summarize the key techniques adopted in the submitted solutions. Finally, we discuss the open issues and the choices of techniques regarding the online deployment.
Teaching Maritime English with Innovative Technologies

The purpose of this paper is to present the past and modernity of the most important seaports of Georgia -Batumi and Poti -and determine their role and place in the economy of the country and in the unified transport system.As the development of Georgia's port potential is closely linked to the country's socio-economic development, its efficient use of geographical location, and the successful functioning of the Eurasian Transport Corridor in general.The history of the creation of Georgia's seaports is practically the history of the formation of the Caucasus Logistics Center, which defined Georgia's role as a transit country.Georgia is an important link of the Europe-Caucasus-Asia Corridor, it is the Transcaucasian maritime gateway.The ports of Batumi, Poti, Kulevi, Supsa and under construction seaport Anaklia are vital strategic facilities that will ensure the country's economic progress.Among its past and contemporaries, the ports of Batumi and Poti are important, as they are distinguished by a number of advantages from the Black Sea ports (water depth, less danger of storms and heat, etc.).In the recent past, they have played an active role not only in the maritime shipping of Georgia and the former Soviet Union, but also in the development of maritime trade and economic ties worldwide.The western part of Georgia has historically been associated with the sea and sea navigation, the myth of the Argonauts, the existence of Greek newborns indicates that maritime navigation in ancient Colchis was one of the major means of leaving the world.Georgia, as a maritime country, was and is a country of great economic potential, to prove this; we will bring some details from its history.