Reviewerly/exHarmony huggingface dataset:
The Productora Cu-Au-Mo deposit: an example of spatially associated magnetite-apatite, tourmaline-cemented breccias and porphyry mineralization

The Productora Cu-Au-Mo deposit is hosted by a Mesozoic hydrothermal breccia complex in the Coastal Cordillara of Region III, northern Chile. Mineralization at Productora extends discontinuously over 8 km in a northeast-oriented corridor. The current resource, which includes the neighboring Alice porphyry Cu-Mo deposit, is estimated at 236.6 Mt grading 0.48% Cu, 0.10 g/t Au, and 135 ppm Mo. The deposit is of significant interest as it presents an example of spatially associated magnetite-apatite mineralization and porphyry-style mineralization. Whilst previous studies have described Productora as an IOCG, we describe the deposit characteristics, based on new information, and present a revised genetic model. Discussion is centered around fluid source and deposit classification as porphyry-related rather than IOCG.
Parallel Sentence Alignment from Biomedical Comparable Corpora.

Parallel sentences provide semantically similar information which can vary on a given dimension, such as language or register. Parallel sentences with register variation (like expert and non-expert documents) can be exploited for the automatic text simplification. The aim of automatic text simplification is to better access and understand a given information. In the biomedical field, simplification may permit patients to understand medical and health texts. Yet, there is currently no such available resources. We propose to exploit comparable corpora which are distinguished by their registers (specialized and simplified versions) to detect and align parallel sentences. These corpora are in French and are related to the biomedical area. We treat this task as binary classification (alignment/non-alignment). Our results show that the method we present here can be used to automatically generate a corpus of parallel sentences from our comparable corpus.
On Construction Internet Site for the Students of Technical University

We consider the construction of an internet site for students of technical university. We use the construction and management of the site program JOOMLA. The site can contain the materials for the students, results of an exam and so on.
Robust Registration of Medical Images in the Presence of Spatially-Varying Noise

Spatially-varying intensity noise is a common source of distortion in medical images and is often associated with reduced accuracy in medical image registration. In this paper, we propose two multi-resolution image registration algorithms based on Empirical Mode Decomposition (EMD) that are robust against additive spatially-varying noise. EMD is a multi-resolution tool that decomposes a signal into several principle patterns and residual components. Our first proposed algorithm (LR-EMD) is based on the registration of EMD feature maps from both floating and reference images in various resolutions. In the second algorithm (AFR-EMD), we first extract a single average feature map based on EMD and then use a simple hierarchical multi-resolution algorithm to register the average feature maps. We then showcase the superior performance of both algorithms in the registration of brain MRIs as well as retina images. For the registration of brain MR images, using mutual information as the similarity measure, both AFR-EMD and LR-EMD achieve a lower error rate in intensity (42% and 32%, respectively) and lower error rate in transformation (52% and 41%, respectively) compared to intensity-based hierarchical registration. Our results suggest that the two proposed algorithms offer robust registration solutions in the presence of spatially-varying noise.
[LETTER] High-efficiency Low-latency NTT Polynomial Multiplier for Ring-LWE Cryptography

This paper presents a novel architecture to perform polynomial multiplication in ring learning with errors (ring-LWE) cryptosystems. By employing number theoretic transform (NTT) of the input polynomials simultaneously, the multiplication latency is significantly reduced. In addition, a multiple-path delay feedback (MDF) architecture is used to speed up the multiplication process. As a result, the proposed NTT multiplier offers a better value of area-latency product compared with that of previous studies. The simulation results for the security parameters n = 512 and q = 12,289 on Xilinx Virtex-7 FPGA show that the proposed multiplier uses only about 8.69% of the number of clock cycles required by previous works to completely perform the polynomial multiplication. Furthermore, the obtained area-latency product value of the proposed architecture is less than 45.3% of that of previous works.
Episodic Mapping Strategy: Structuring Students’ Reading Comprehension

This research investigated the effect of Episodic Mapping strategy on students’ reading comprehension in narrative text. It examined the difference of students’ reading comprehension before and after using the Episodic Mapping strategy. Quasi-experiment with nonequivalent control group was used as design of this research. 70 students of a Senior High School in Indonesia were selected by using cluster random sampling. The data was obtained from multiple choice test and analyzed by Independent sample t test. As results, the experimental group performed better than the other at posttest stage. In addition, students at experimental group developed their reading comprehension by extracting text structure. Hence, Episoding mapping strategy significantly reinforces students’ reading comprehension.
Peer to Peer Deaf Multiliteracies:Towards a Sustainable Approach to Education in Ghana

In Ghana as many other countries in the global South, many children and young people are marginalized in education. From a pilot project we had learnt from our work in India that an approach based on “real literacies”, in which links are made to authentic literacies in the environment, with teaching and support by deaf peer tutors and deaf research assistants, was fruitful. That pilot also included consultations with the deaf community in Ghana. The project reported upon here, “Peer to peer deaf multiliteracies: research into a sustainable approach to education of Deaf children and young adults in developing countries “ (P2PDML) extended the principles to include young children as well as adults and was reconceptualised upon the richer foundation of multiliteracies, embracing available semiotic repertoires and means of learning. This paper presents three multimodal vignettes which illustrate the dynamic combinations of modes utilized in effective pedagogic activities and gives a flavour of the project’s approaches to peer tutoring and documentation of activities. Finally, in line with the conference theme, “The power and possibilities for the public good when researchers and organizational stakeholders collaborate” we also report on our engagement with significant stakeholders.
Online teaching — systems approach: questions and answers

At a recent International Forum on Teacher Education (Kazan,&#x0D; Russia, May 27–29, 2020), special sessions were devoted to questions related to online teaching – in view of the recent forced world-wide transition to online-only education. This article summarizes, in a systematic way, issues discussed at these sessions.
Physics and Mathematics Basics

This chapter covers a few basic areas of physics and mathematics that are important for science and engineering, namely, temperature, force, pressure, and some general algebra/statistics concepts. Why are these areas so important? Because they govern the physical world and how many things work or behave. Understanding of these tools can provide the background to ways of improving life, increasing energy efficiency, improving products, increasing safety, and other innumerable facets of life.
Grounds for the Emergence of Individual Labor Relations with Managers and Artistic Staff of Cultural Institutions

Problem setting. In recent years, the introduction of urgent formats to attract citizens to work in Ukraine has become popular. Spheres of activity in which legal forms are traditionally applied, are calculated for functioning of indefinite labor relations (the labor contract is concluded for an indefinite period) (part 1 of the paragraph. 1 article. 23 labor Code) both in Ukraine and the EU countries, gradually changing to legal forms that serve their purpose temporary short-term labor relations; fixed-term labor contracts (part 1 paragraph. 2, 3 art. 23 labor Code); contracts (part 3 art. 21 labor Code). Target of research. The purpose of this article is to identify conflicts, gaps in Ukrainian legislation that regulates the sphere of culture, which create problems in the regulation of the employment relationship between the professional creative workers and leaders of cultural institutions, development of proposals on elimination of these shortcomings in the legal regulation of employment relationship and providing protection and guarantees of artistic and artistic staff in this area. Analysis of resent researches and publications. Theoretical problems of forms of realization of the right to work, the bases of emergence of labor relations were investigated by O. I. Protsevsky, V. V. Eremenko, P. D. Pilipenko, L. V. Solodovnik, K. Yu. Melnik and others. Such scientists as S. M. Prilipko, A. V. Andrushko, N. M. Neumyvaychenko, K. V. Kholodova. E.B. Khokhlov, A. O. Movchan, N. P. Mokritskaya, A.V. Bykova, directly studied the features of the grounds for the emergence of labor relations with certain categories of workers, and regarding the sphere of culture-O. A. Menska, I. B. Tatsishin. Article’s main body. This article investigates features of legal forms of realization of the right to work in the field of culture, the opening up of the legal grounds for the employment relationship with managers and artistic staff of cultural institutions to define the issues of the competitive selection, contracting and appointment as legal facts linked with the emergence of labor relations of these categories of workers. Recommendations for amendments to the legislation that regulates labor in the field of culture are made on the basis of the findings. Conclusions and prospects for the development. As given the above, it can be argued that changes to the text of article 21 of the law of Ukraine “On culture” dated January 28, 2016 No. 955-VIII regarding the implementation of the contract for creative workers in cultural institutions, according to legal form and content are not legal and constitutional, as directly violate the right to work art and artistic personnel of cultural institutions in the application of contractual forms of forced restriction of duration of labour relations that objectively ( according to the nature of work and General rules) continue indefinitely. The author proposes to make appropriate changes to the current legislation in order to eliminate existing conflicts and gaps.
Interpreting natural structures and systems through visual traces

I came to appreciate mathematics decades after my compulsory high-school math lessons were over. With a longer life experience, I came to see that math can be a fascinating and beautiful intellectu...
A Study of technologies to further research in Health Care Data Security in Medical Report using Block Chain

In today's healthcare system one of the most important requirement is to protect the data of patient's medical report against potential attackers.This is basic to secure information that can just approve people can get to the patient's medical report.To grant the security for the data of the patient we proposed Block Chain technology.Which is decentralized architecture, where data is stored in from of blocks for processing.In this health care sector the security of patient data is to be maitained.This block chain is composed in three phases: 1. Authentication-we use Quantum Cryptography, 2. Encryptionwe use AES and for, 3. Data Retrievalwe use SHA algorithms are used to resist the frequent attacks.This framework ensure the protection of the patients and moreover keeps up the security and trustworthiness of the health care system.
Automatically batching control-intensive programs for modern accelerators

We present a general approach to batching arbitrary computations for accelerators such as GPUs. We show orders-of-magnitude speedups using our method on the No U-Turn Sampler (NUTS), a workhorse algorithm in Bayesian statistics. The central challenge of batching NUTS and other Markov chain Monte Carlo algorithms is data-dependent control flow and recursion. We overcome this by mechanically transforming a single-example implementation into a form that explicitly tracks the current program point for each batch member, and only steps forward those in the same place. We present two different batching algorithms: a simpler, previously published one that inherits recursion from the host Python, and a more complex, novel one that implemenents recursion directly and can batch across it. We implement these batching methods as a general program transformation on Python source. Both the batching system and the NUTS implementation presented here are available as part of the popular TensorFlow Probability software package.
Aplikasi Sistem Pendaftaran Jasa Pelatihan Setir Mobil Berbasis Web Pada LPK DELTA Kulon Progo

The registration process on LPK DELTA is still done by coming directly to the office to register as a member. This is an obstacle for applicants whose regions are outside&#x0D; Kulon Progo. Another problem is that there is often an error in scheduling steering wheel training and obstacles in the storage process because it requires a large amount of storage space. This web-based car steering course application is the right solution to solve the problems that exist in LPK DELTA. In designing the steering wheel course system, this method uses research methods, namely data collection methods such as observation, interviews, literature studies and waterfall development methods. This steering wheel course application uses XAMPP software, Adobe Dreamweaver CS6 and uses programming languages such as HTML, PHP, CSS, and JavaScript. Testing this website using blackbox testing. From the results of the writing it can be concluded that the existence of this website as a medium of information and promotion to users and can facilitate the registration system and confirmation of payment of car steering training services online, minimize errors in registration, course scheduling, and accumulation of registration files because they are well managed and stored in the company database.
Health Data Sharing using Blockchain

In the present computerized society, everybody is worried about the protection and security of their information, particularly in human services.So we need more straightforwardness in clinical data to ensure patients' protection and decrease conceivable security penetrates.Individuals these days are faking their wellbeing status and issues to guarantee medical coverage while some likewise phony clinical cases to guarantee false advantages. These cases, when indicted, become muddled because of the absence of legal framework affirmations. The inspiration of this venture is to plan a clinical information sharing plan dependent on blockchain. It is useful to the capacity, the executives, and sharing of the clinical information. The plan ought to fulfill the security prerequisites in clinical information sharing plans. A lightweight clinical information sharing and security model is proposed, the model could make information sharing among specialists from various emergency clinics. The put away clinical data is exceptionally secure and couldn't be effortlessly altered since they are put away in the blockchain. An improved accord instrument is proposed by improving the customary appointed proof of stake. It is secure, solid, and effective. Blockchain empowers the sharing of data on a protected, sealed, and changeless stage. Nothing can be altered or falsely passed on in the Blockchain record. When the record is spared, it is effectively certain, remains in the framework, and is effectively available.
REAL-TIME DEVELOPMENT OF EMBEDDED SYSTEM: TARGETTING AND CONTROL SYSTEMFOR SEMI-BALLISTIC VEHICLE FOR RAPID AND PRECISE SEARCH AND RESCUEAPPLICATIONS

The Philippines is one of the most disaster-ridden nations on the western edge of the Pacific and along the circum-pacific seismic belt, or is calledthe Ring of Fire, which makes our nation powerless against an assortment of cataclysmic events. As a calamity-oriented country, this investigationconsidered the use of Unmanned Aerial Vehicles (UAV) to improve information. This paper is talks about the massive advance in the development ofintegrated system applications. Inserted System is a piece of equipment that incorporates hardware and product programming. It has been widelyused and its plan has become a significant field of control design, notwithstanding the provision of a constant correspondence framework forobservation, follow-up and verification of applications. The control framework runs on the installed equipment stage, which incorporates themicrocontroller, the sensors used for route and natural checks and remote correspondence. The plan recalls the operation of the UAV for its properoperation and the establishment of secure flight controls under temperamental conditions. In addition, the project considers the best way to achievethe modification process by finding the most appropriate method of repairing wings using methods for height, length and mental edges (Heading,Pitch, and Roll) and successful paths from the target. The system is ideal for collecting, discharging and analyzing data from a few tools mounted inan unmanned aerial vehicle.
The Power of Suggestion

Multiagent teams have been shown to be effective in many domains that require coordination among team members. However, finding valuable joint-actions becomes increasingly difficult in tightly-coupled domains where each agent's performance depends on the actions of many other agents. Reward shaping partially addresses this challenge by deriving more tuned rewards to provide agents with additional feedback, but this approach still relies on agents randomly discovering suitable joint-actions. In this work, we introduce Counterfactual Agent Suggestions (CAS) as a method for injecting knowledge into an agent's learning process within the confines of existing reward structures. We show that CAS enables agent teams to converge towards desired behaviors more reliably. We also show that improvement in team performance in the presence of suggestions extends to large teams and tightly-coupled domains.
Empirical Evaluation of the Effectiveness of Variational Autoencoders on Data Augmentation for the Image Classification Problem

In the last decade, deep learning methods have become the key solution for various machine learning problems.One major drawback of deep learning methods is that they require large datasets to have a good generalization performance.Researchers propose data augmentation techniques for generating synthetic data to overcome this problem.Traditional methods, such as flipping, rotation etc., which are referred as transformation based methods in this study are commonly used for obtaining synthetic data in the literature.These methods take as input an image and process that image to obtain a new one.On the other hand, generative models such as generative adversarial networks, auto-encoders, after trained with a set of image learn to generate synthetic data.Recently generative models are commonly used for data augmentation in various domains.In this study, we evaluate the effectiveness of a generative model, variational autoencoders (VAE), on the image classification problem.For this purpose, we train a VAE using CIFAR-10 dataset and generate synthetic samples with this model.We evaluate the classification performance using various sized datasets and compare the classification performances on four datasets; dataset without augmentation, dataset augmented with VAE and two datasets augmented with transformation based methods.We observe that the contribution of data augmentation is sensitive to the size of the dataset and VAE augmentation is as effective as the transformation based augmentation methods.
Decentralised Runtime Norm Synthesis

The process of determining the appropriate set of norms, referred to as synthesis, for a multiagent system has predominantly been carried out offline by the designers of the system. Of recent, there have been a few approaches that synthesise norms online utilising a centralised mechanism. The research presented here aims to propose a mechanism for decentralised runtime (online) norm synthesis through the use of agents dedicated to synthesising norms based on participating agents' requests.
Yesterday's Reward is Today's Punishment: Contrast Effects in Human Feedback to Reinforcement Learning Agents

Autonomous agents promise users of a personalized future, allowing them to direct their attention to tasks most meaningful to them. However, the demands of personalization stand unfulfilled by current agent training paradigms such as machine learning, which require many orders of data to train agents on a single task. In sequential decision making domains, Reinforcement Learning (RL) enables this need, when a priori training of desired behaviors is intractable. Prior work has leveraged user input to train agents by mapping them to numerical reward signals. However, recent approaches have identified inconsistent human feedback as a bottleneck to achieving best-case performance. In this work, we present empirical evidence to show that human perception affected by contrast effects distorts their feedback to Reinforcement Learning agents. Through a set of studies involving 900 participants from Amazon Mechanical Turk who were asked to give feedback to RL agents, we show that participants significantly underrate an agent's actions after being exposed to an agent of higher competence on the same task. To understand the significance of this effect on agent performance during training, we then simulate trainers that underrate actions of an agent based on past performance - creating a systematically skewed feedback signal - integrated into an actor-critic framework. Our results show that agent performance is reduced by up to 98% in the presence of systematic skews in human feedback in Atari environments. Our work provides a conceptual understanding of a source of inconsistency in human feedback, thus informing the design of human-agent interactions.
Dynamic and Accelerated Partial Order Planning for Interactive Narratives

This paper explores new narrative generation paradigms for open world problems. We propose a speed-up variant of partial planner–accelerated partial order planner, that can automatically generate narratives for large plan spaces. To incorporate real-time free-form user interaction, a dynamic partial planning technique has been introduced to self-repair the narratives. We also propose a scalable and robust framework to craft open world narratives with minimal effort. Our approach enables content creators to craft complex open world narratives without explicitly authoring user interaction arcs. We tested our framework by developing multiple narratives with free-form interactions. Those narratives were used to test the robustness of the proposed planners.