Reviewerly/exHarmony huggingface dataset:
Implementing a Work Program Monitoring Information System (Case Study at PT Telkom Tbk)

This research was conducted by purposed to gained knowledge regarding process of implementing the work programs which carried out by PT. Telkom, especially at Network Division of Central Jakarta area around these days. while Analyze these work program system and create WEB-based work program to monitoring system according to company requirements and regulations. PT. Telkom, especially Network Division of Central Jakarta area, which engaged in telecommunications and has the main duty as operation and maintenance of equipment that owned by PT. Telkom, especially Network Division at Central Jakarta area, so it could keep the assets owned by company always operating normally. According to research that carried out by employees itself, there are so many problems in creating work programs cause it was still manual, Assistant Manager of Network Area were difficulty to monitoring the development of work programs and report the results aswell it was because there has no integration in one application system, Analysis and this pattern of information system by object-oriented methods with UML notations. With web-based work program monitoring information system, it was expected that it could be a solution to sort of problems that faced in process of implementing work programs.
Conflict educational environment as a factor hindering creativity development of participants in the educational process

The aestheticization of the educational environment is inseparable from the formation of the morality of the individual, the creative orientation of its development, as it is the aesthetic beginning in a growing person is the core of the formation of his culture.
Stable Policy Optimization via Off-Policy Divergence Regularization.

Trust Region Policy Optimization (TRPO) and Proximal Policy Optimization (PPO) are among the most successful policy gradient approaches in deep reinforcement learning (RL). While these methods achieve state-of-the-art performance across a wide range of challenging tasks, there is room for improvement in the stabilization of the policy learning and how the off-policy data are used. In this paper we revisit the theoretical foundations of these algorithms and propose a new algorithm which stabilizes the policy improvement through a proximity term that constrains the discounted state-action visitation distribution induced by consecutive policies to be close to one another. This proximity term, expressed in terms of the divergence between the visitation distributions, is learned in an off-policy and adversarial manner. We empirically show that our proposed method can have a beneficial effect on stability and improve final performance in benchmark high-dimensional control tasks.
Legendre Based Adaptive Image Segmentation Combining The Gradient Information

In this paper, we propose an adaptive variable exponent level set method based on Legendre polynomials for object segmentation in complex visual environment. First, we use a set of Legendre basis functions to approximate the region intensity, which enable us to accommodate heterogeneous objects. Second, an improved function is presented to update exponent adaptively and ensures the image gradient information embedding into the model easily. The proposed method is robust to low contrast, blurred boundaries, noise and the 10-cation of initial contour, and sufficient in handling large scale intensity variations. Experimental results demonstrate that the proposed method can achieve relatively high segmentation accuracy and less computational time.
Digital Branch: Learn English: Home

Learn speaking, listening, reading, and writing at our Learn English Conversation Group sessions. Our class sizes are small. Sessions are free.
Denoising of Images Using Autoencoder

Image is the object that stores and reflects visual perception. Images are also important information carriers today. Acquisition channel and artificial editing are the two main ways that corrupt observed images. The goal of image restoration technique is to restore the original image from a noisy observation of it which is aiming to reconstruct a high quality image from its low quality observation has many important applications, like low-level image processing, medical imaging, remote sensing, surveillance, etc. Image denoising is common image restoration problems that are useful by many industrial and scientific applications. The application classifies images based on single image selected from user. The noise from the corrupted image is removed and original clear image is obtained. In our project we are making use of Auto-encoder. Auto-encoder do not need much data pre-processing and it is an end to end training process which helps to remove the noise present in some pictures using some data compression algorithms.
Algorithmic antitrust (London, 6 March 2020)

On the 6th of March 2020, few days before the Covid-19 lockdown, LL.M. Programme Director Dr Aurelien Portuese has convened a conference on “Algorithmic antitrust” in the Waldegrave Drawing Rooms…
Linear Space-Invariant System Identification And Mismatch Bounds For Estimation Of Dynamical Images

For linear space-invariant temporal systems, we provide a lower bound on the penalty incurred by approximating system dynamics in a Kalman filter by a random walk model, a common model when dynamics are unknown. We then present a computationally tractable algorithm for system identification of high-dimensional linear space-invariant dynamical systems, whereby the circulant structure of the state transition operator yields an estimate of the governing dynamics from a small number of temporal steps. By completing all operations in the frequency domain, we efficiently provide an estimate of the system dynamics and the state of the system. The estimation of system dynamics greatly improves the state estimation over the random walk model, suggesting classical estimators may remain applicable in modern imaging tasks.
Blockchain

Say the word “blockchain” and thoughts immediately turn to cryptocurrencies and nefarious financial dealings. However, readers of Blockchain will discover that this open, decentralized technology h...
Matching Questions and Answers in Dialogues from Online Forums

Matching question-answer relations between two turns in conversations is not only the first step in analyzing dialogue structures, but also valuable for training dialogue systems. This paper presents a QA matching model considering both distance information and dialogue history by two simultaneous attention mechanisms called mutual attention. Given scores computed by the trained model between each non-question turn with its candidate questions, a greedy matching strategy is used for final predictions. Because existing dialogue datasets such as the Ubuntu dataset are not suitable for the QA matching task, we further create a dataset with 1,000 labeled dialogues and demonstrate that our proposed model outperforms the state-of-the-art and other strong baselines, particularly for matching long-distance QA pairs.
PHYSIOTHERAPY PERFORMANCE AND MANAGEMENT IN HOSPITAL DURING SARS-COV-2 (COVID-19) PANDEMIC: THE IMPORTANCE AND CHALLENGES OF REHABILITATION / DESEMPENHO E GESTÃO DA FISIOTERAPIA NO HOSPITAL DURANTE A PANDEMIA DO SARS-COV-2 (COVID-19): A IMPORTÂNCIA E OS DESAFIOS DA REABILITAÇÃO

Human society is experiencing intense social changes caused by the new Coronavirus (SARS-CoV-2) pandemic. The disease caused by the new Coronavirus (COVID-19) and facing a scenario of fear and high mortality rates, adaptations were necessary in several sectors, especially in health. COVID-19 causes acute respiratory distress syndrome (ARDS). The consequence for infected individuals is the search for medical services, and for more serious cases, it is admitted to an Intensive Care Unit (ICU), given the seriousness and compromise of the case. Based on all the signs and symptoms and evolution of COVID-19, strategies are necessary to alleviate and treat the individual's clinical condition. Thus, physiotherapy is able to significantly minimize the consequences of all sequelae resulting from the hospitalization process, promoting faster functional recovery and, if necessary, providing care to reverse the pulmonary impairment that the infected individual may have.
Personal Trackers: A Potential Aid to Home Quarantine in India

During this Covid19 pandemic, millions of people have been affected globally. Social distancing and quarantining have been the most important modalities adopted to control the transmission of the disease in the community. Government of India has laid down strict regulations for quarantining individuals and the efforts have definitely made a huge difference in controlling the spread of the disease so far. Nevertheless, in the current approaches adopted to home quarantine individuals, there are several drawbacks, which include violence against healthcare workers, shortage of PPE, and misleading of officials by the quarantined individuals, and these methods also would require huge manpower for its functioning. Hence, personal tracking of quarantined individuals using tamperproof wristbands could be a more efficient and cost-effective solution that could prove more advantageous to the current methods adopted. Key words: Covid-19, Quarantine, Technology
(Green) Planets in a Room

&amp;lt;p&amp;gt;Planets in a room (PIAR) is a DIY kit to build a small, lowcost spherical planet simulator and planetarium projector. Teachers, science communicators that run a small museum or planetarium, planetary scientists, geologists and other individuals can easily build it and use it on their own, to show and teach the Earth and other planets and to develop and share material with a growing online community. (http://www.planetsinaroom.net/)&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The project is being developed by the italian non-profit association Speak Science, with the collaboration of the Italian National Institute for Astrophysics (INAF) and the Roma Tre University, Dipartimento di Matematica e Fisica.&amp;amp;#160;&amp;lt;br&amp;gt;It was funded by the Europlanet Outreach Funding Scheme &amp;amp;#160;and &amp;amp;#160;was presented to the scientific community at EPSC (European Planetary Science Congress) in 2017 and 2018. Today it is being distributed to an increasing number of schools, science museum and research institutions from all over Europe. PIAR is also one of the projects selected by the new-born Europlanet Society for education and public outreach of planetary science.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;At EGU2020, we will present an improved, new version of the project. Having started with 3d-printed technology, &amp;amp;#160;PIAR is today going green,&amp;amp;#160; with a new wooden, plastic-free version of the kit that will be presented for the first time.&amp;amp;#160;&amp;lt;br&amp;gt;To help you engage a larger audience, we will also present a selection of educational material and projects that have been developed for PIAR by scientists, teachers and communicators &amp;amp;#160;and that are focused on Earth and on planetary habitability inside and outside the Solar System.&amp;lt;/p&amp;gt;
Att designa en toalett är inte skitlätt : Hur behov och inkludering samsas vid utformningen av en handikapptoalett

This thesis work in information design with a focus on spatial design is about how people's needs, in addition to the natural ones, can be considered in a handicap toilet to include a broader targe ...
Inclusive Institutions – a Precondition of Sustainable Development. A Comparative Analysis Between Romania and Poland

When trying to identify the sources of growth and sustainable development, institutions and their effectiveness are among the most important and powerful instrument required to explain the economic dynamics of countries all over the world. More precisely, those rules, formal or informal, political or economic, that foster the participation of the majority of people in activities able to ensure the allocation of resources to their most productive destinations are the ones that promote long-term prosperity. Their significance is becoming even more important when the particular case of transition economies is addressed. Consequently, the aim of this paper is to demonstrate that inclusive institutions (political and economic ones) are a prerequisite for the long-run development, mainly for emerging economies. Using an unique dataset of indicators that highlight the quality of economic and political institutions we have employed a VEC Model, variance decomposition and Granger causality analysis for Romania and Poland, in order to emphasize that, from a comparative perspective, each transition path towards the market economy has designed different rules of the game determining, thus, dissimilar development profiles.&#x0D; Keywords: Sustainable development, Transition economies, Institutions, Institutional performance
Persepsi Anggota Polisi terhadap Perpustakaan Kepolisian Daerah Sumatra Barat dalam Memenuhi Kebutuhan Informasi

AbstractThe writing of this paper discusses the perception of police members of the West Sumatra Regional Police Library in meeting information needs. This type of research is a descriptive study with a quantitative approach. The population of this study is approximately 200 people. From this population samples were taken using the Slovin formula, so based on calculations, a sample of 67 people can be taken. The sampling method is the probability sampling method. Data collection techniques using a questionnaire, containing three indicators which are broken down into 13 statement items. The data analysis technique uses a Likert scale.Based on the results of data analysis in this study, it can be concluded that, among others: first, the perception of police members of the collections available at the West Sumatra Police Library is good. (a) the available collection is complete; (b) available collections have various titles; (c) available collections already meet the user's information needs; (d) available collections are easy to find; (e) the available collection is always increasing; (f) available collections relevant to the needs of users; (g) available collection is up to date; (h) collections available at the West Sumatra Regional Police Library are print only, non-print collections available; (i) and respondents state that libraries need to provide digital services to meet information needs. Second, the perception of service satisfaction; (a) librarians have helped users in finding information; (b) librarians understand the needs of users; (c) the librarian is responsive in providing assistance; (d) and the librarian is friendly in serving. However, the West Sumatra Regional Police Library is still empty of visitors. The lonely visit to the West Sumatra Regional Police Library was caused by the lack of time for police officers to visit the library, the low interest in reading police members, and there were other places besides the library to search for information. One of them, the electronic media to find information quickly.Keywords: perceptions, members of the police, information need
Computational Analysis of Arabic Cursive Steganography using Complex Edge Detection Techniques

Arabic language contains a multiple set of features which complete the process of embedding and extracting text from the compressed image.In specific, the Arabic language covers numerous textual styles and shapes of the Arabic letter.This paper investigated Arabic cursive steganography using complex edge detection techniques via compressed image, which comprises several characteristics (short, medium and Long sentence) as per the research interest.Sample of images from the Berkeley Segmentation Database (BSD) was utilized and compressed with a diverse number of bits per pixel through Least Significant Bit (LSB) technology.The method presented in this paper was evaluated based on five complex edge detectors (Roberts, Prewitt, Sobel, LoG, and Canny) via MATLAB.Canny edge detector has been demonstrated to be the most excellent solution when it is vital to perform superior edge discovery overcompressed image with little several facts, but Sobel appears to be better in term of the execution time for Long sentence contents.
Enforcing Security and Privacy in Distributed Ledgers Using Intel SGX

Distributed Ledger Technology (DLT) utilizes an architecture that can host a large number of nodes without pre-established trust to provide decentralized services. The blockchain is the most widely used architecture of distributed ledger, where transactions across the whole network are visible to all participants in a chain to prevent tampering. However, transactions may contain sensitive information such as business contract. To secure the system and protect user privacy, we propose a multi-channel architecture that leverages Intel Software Guard Extensions (SGX). We illustrate how SGX capabilities help to defend against attacks on distributed ledgers, by way of SGX enforcement on the participating machines. We adopt the design and implementation of a two layer architecture for securing the blockchain mining process and enhancing the transaction privacy. The security analysis and performance evaluation show that the design and protocols are capable of protecting privacy, defending against adversarial attacks and scalable.
Generative Adversarial Networks for Mitigating Biases in Machine Learning Systems.

In this paper, we propose a new framework for mitigating biases in machine learning systems. The problem of the existing mitigation approaches is that they are model-oriented in the sense that they focus on tuning the training algorithms to produce fair results, while overlooking the fact that the training data can itself be the main reason for biased outcomes. Technically speaking, two essential limitations can be found in such model-based approaches: 1) the mitigation cannot be achieved without degrading the accuracy of the machine learning models, and 2) when the data used for training are largely biased, the training time automatically increases so as to find suitable learning parameters that help produce fair results. To address these shortcomings, we propose in this work a new framework that can largely mitigate the biases and discriminations in machine learning systems while at the same time enhancing the prediction accuracy of these systems. The proposed framework is based on conditional Generative Adversarial Networks (cGANs), which are used to generate new synthetic fair data with selective properties from the original data. We also propose a framework for analyzing data biases, which is important for understanding the amount and type of data that need to be synthetically sampled and labeled for each population group. Experimental results show that the proposed solution can efficiently mitigate different types of biases, while at the same time enhancing the prediction accuracy of the underlying machine learning model.
Foreign Language Anxiety in Student’s Speaking and Writing Skills

The objective of this research was on the level of Foreign Language Anxiety that experienced by students. In this research, the researcher was use the Qualitative research as the method in implementing case study. The sources of data were 30 students of the second semester of Banten Jaya University. For collecting data that used in this study include classroom observation, questionnaires and interview. The questionnaire used to obtain specific information data was gathered from the participants by FLCAS of Horwitz et all (1986). From the result of FLCAS questionnaire, there were 10 students who felt very anxious with percentage 33.33%, 8 students felt anxious with the percentage 26.67%, 8 students felt mildly anxious with the percentage 26.67%, 4 students felt relaxed with the percentage 13.33% and there was no student who felt very relaxed. Then, the result of WAT questionnaire were 7 students felt very anxious with percentage 23.33%, 8 students felt anxious with the percentage 26.67%, 9 students felt mildly anxious with the percentage 30%, 6 students felt relaxed with the percentage 20% and there was no student who felt very relaxed. Based on the findings of the present study, several conclusions can be made: First, students’ anxiety in speaking showed that the students never felt quite sure of themselves when they were speaking in foreign language class. Second, students’ anxiety in writing above showed that most of students avoided writing in English.
Dynamic panel estimation models and foreign direct investment in developing countries

This paper employs the dynamic panel estimation models to provide an empirical update for the investigation of globalisation, corruption, economic freedom and foreign direct investment (FDI). Previous research examined the relationships between FDI and gross domestic product, economic freedom index, corruption perception index, social globalisation index, and political globalisation index. Our current research contributes to the existing literature by employing dynamic panel estimation models to investigate the relationships, using data for 1996-2016, and generating more solid research outcomes on the determinants of FDI for developing countries.
OPINION ANALYSIS OF TWITTER DATA USING MACHINE-LEARNING TECHNIQUE

Online Micro blogging on casual associations have been used for exhibiting sentiments about certain substance in very short messages. Existing notable small scale websites like twitter, facebook and so forth, in which twitter accomplishes most prominent proportion of thought in the field of examination locales related to thing, film reviews, stock exchange, etc. The assessment on feeling investigation has been going for a long time. Assumption investigation in present days transforms into the major issue in field of examination and advancement. In view of bit by bit increase in the amount of clients on the long range casual correspondence destinations, huge proportion of data conveys as substance, sound, video and pictures. There is have to do estimation analysis as writings in type of messages or presents on discover the whether the opinion is negative, positive or unbiased. We had separated information from twitter for example movie surveys for feeling forecast utilizing machine-learning calculations. We associated managed AI counts like Support vector machines (SVM), most extreme entropy and Naive Bayes to describe data using unigram, bigram and cross variety for instance unigram + bigram features. Result demonstrates that SVM outperformed different classifiers with striking precision of 87% for filmaudits.