Reviewerly/exHarmony huggingface dataset:
A new statistical approach to the geochemical systematics of Italian alkaline igneous rocks

Abstract The ultra-alkaline rocks have exotic features that frustrated many attempts to group them in a single classification diagram. A consistent classification would be very useful to define a possible consanguinity, an argument that feed a living debate. This paper investigates the petrologic characteristics of the Cenozoic Italian ultra-alkaline rock-suite using -Rank Entropy Anentropy (RHA) and Principal Component Analysis (PCA)-. The RHA formula is the succession of component’s symbols arranged according to the diminishing of their elemental content in the analysis (whole rock composition). Other two parameters considered are an expression of the anentropy and entropy of the system. The PCA allows the definition of new latent variables based on geochemical compositions through linear combinations of the major oxides. Using both statistical methods was possible to create discrete groups of rock-types, associated by genetic relationship. The groups plotted in the Mg-Ca-Al ternary diagram depicts two main evolutionary arrays. We interpret the chemical variance in term of a general magmatic processes based on immiscibility and crystal fractionation. A comparison with similar association worldwide give a more general prospective to the magmato-tectonic assignment of these rocks, which is highly controversial in Italy.
Job seeker information system using online web based and android mobile phones

Abstract In this era of globalization, information technology is very important in the need for accurate, precise and fast information in presenting very complete data and this is one of its important objectives. For this reason, information technology plays an active role in all fields, especially this time in presenting data about Minahasa Regent unemployment that searching for a job, and all information relating to it. The development of internet technology, society is increasingly facilitated in doing several processes, one example is registration of prospective This study uses a Prototype development model that has 3 Stages, namely Listening to Customers, Building to improve prototypes, Customers testing prototypes. Application trials are conducted using Black Box Testing where there are 3 types of trials conducted by the author, namely Developer Test, User admin test, User community test workers who can done by opening the company’s website or job vacancy provider services. Primary data collection is done by in-depth interviews using open-ended questions and observation with critical incident techniques. In this study it was concluded that, Web-based Information System Design, is actually very necessary to find out various kinds of unemployment data and activities around Minahasa Regent. This process made easier because of registrants do not have to come directly to the company or service the provider of the vacancy in question to do the registration process so will automatically save time and costs issued by the registrant. This research will developing a software design and manufacturing web-based process that can do registration and selection of recruitment of prospective workers work online. Also provided information services for prospective workers, among other things, look at the announcement of vacancies work, see the results of the selection of admission of candidates online workforce. So the process recruitment of prospective workers by companies that concerned can be held more transparent, and able to increase interest from prospective workers because of the ease of the process registration.
QCI Qbsolv Delivers Strong Classical Performance for Quantum-Ready Formulation

Many organizations that vitally depend on computation for their competitive advantage are keen to exploit the expected performance of quantum computers (QCs) as soon as quantum advantage is achieved. The best approach to deliver hardware quantum advantage for high-value problems is not yet clear. This work advocates establishing quantum-ready applications and underlying tools and formulations, so that software development can proceed now to ensure being ready for quantum advantage. This work can be done independently of which hardware approach delivers quantum advantage first. The quadratic unconstrained binary optimization (QUBO) problem is one such quantum-ready formulation. We developed the next generation of qbsolv, a tool that is widely used for sampling QUBOs on early QCs, focusing on its performance executing purely classically, and deliver it as a cloud service today. We find that it delivers highly competitive results in all of quality (low energy value), speed (time to solution), and diversity (variety of solutions). We believe these results give quantum-forward users a reason to switch to quantum-ready formulations today, reaping immediate benefits in performance and diversity of solution from the quantum-ready formulation,preparing themselves for quantum advantage, and accelerating the development of the quantum computing ecosystem.
Investigations on Phoneme-Based End-To-End Speech Recognition.

Common end-to-end models like CTC or encoder-decoder-attention models use characters or subword units like BPE as the output labels. We do systematic comparisons between grapheme-based and phoneme-based output labels. These can be single phonemes without context (~40 labels), or multiple phonemes together in one output label, such that we get phoneme-based subwords. For this purpose, we introduce phoneme-based BPE labels. In further experiments, we extend the phoneme set by auxiliary units to be able to discriminate homophones (different words with same pronunciation). This enables a very simple and efficient decoding algorithm. We perform the experiments on Switchboard 300h and we can show that our phoneme-based models are competitive to the grapheme-based models.
Demoting Racial Bias in Hate Speech Detection

In current hate speech datasets, there exists a high correlation between annotators' perceptions of toxicity and signals of African American English (AAE). This bias in annotated training data and the tendency of machine learning models to amplify it cause AAE text to often be mislabeled as abusive/offensive/hate speech with a high false positive rate by current hate speech classifiers. In this paper, we use adversarial training to mitigate this bias, introducing a hate speech classifier that learns to detect toxic sentences while demoting confounds corresponding to AAE texts. Experimental results on a hate speech dataset and an AAE dataset suggest that our method is able to substantially reduce the false positive rate for AAE text while only minimally affecting the performance of hate speech classification.
Derin Kalıntı Ağ Mimarisi Kullanarak Portre Görüntülerinin Bölütlenmesi

Segmenting portrait images into semantic areas is an important step towards scene understanding and image analysis.Although segmentation is a very active field of study, there are few studies in the field of portrait segmentation.One of the most crucial steps in portrait segmentation is the precise segmentation process where semantically related pixels grouped together including hair, face, body, and background.However, this is a challenging problem due to the extreme variations in hair shape, color, and background.In order to handle such variations, we proposed a deep residual network based on ERFNet architecture.We used geometrically normalized faces as an input for the network.Experimental studies on EG1800 dataset (two-classes) and LFW Part Labels Dataset (three-classes) showed that the proposed method provides state of the art mIoU (mean intersection over union) and pixel-based accuracy.We obtained 96.37% mIoU and 98.17% pixel based accuracy for EG1800 dataset and 90.1% mIoU and 97.14% accuracy for the LFW dataset.
Photovoltaic Solar Systems in Multi-Headquarter Institutions: A Technical Implementation in Northeastern Brazil

The use of photovoltaic solar technology is increasingly widespread and consolidated worldwide, gaining significant interest in Brazil. Thanks to records of gradual photovoltaic system price decreases and the construction of legal frameworks favorable to their diffusion, urban and rural residential consumers, service companies, industries, and the government are progressively adhering to the use of this technology. In this context, it is important that institutions and companies with multiheadquarters discern whether it is more advantageous, from both a technical and economic point of view, to disperse photovoltaic systems throughout all of their headquarters or to centralize them in the offices presenting the best energy efficiency. The present study aims at answering this question. To this end, indicators recorded in the Institute of Education Science and Technology (IFRN)-Solar Project implemented by the Rio Grande do Norte Federal Institute of Education, Science and Technology, in Brazil, where 2 MWp of photovoltaic solar energy are installed in 19 of its 22 headquarters, were evaluated. The PVWatts Software, energy measurements at the different plant installation locations and technical performance parameters recurrent in the literature, as well as the Discounted Payback Method were used herein. The results indicate that system centralization in the best-evaluated sites (7 campi) will, in 25 years, provide a 9.07% energy supply gain, a 112.96% financial gain, and a payback reduction of 8.9 years when compared to the alternative comprising generation unit dispersion throughout the 19 campi.
Aspects of choosing by applicants a secondary special or higher education institution

A brief overview of the modern system of secondary special and higher education in the Russian Federation has been given. The problem of competitiveness of educational institutions in the Russian Federation and the world in General has been raised. Statistical data conducted at the end of 2019 questionnaires among the students of the Department of Advertising and Public Relations the State University of Management (Moscow) and students of the Faculty of Advertising and Internet Communications, the International College of Arts and Communications (Moscow). The influence of several factors on the choice by learners of studying educational institutions has been explored, key factors for choice has been highlighted. The opinions of students in terms of the applicability of disciplines in their future profession, assessment of students of the faculty of the institution, the relevance of the cost of education quality and prospects for future employment in the profession after graduation have been analysed. According to the results of the survey, answers were given to such questions as: how do applicants themselves choose an educational program – their future profession? How do they perceive the educational service provided to them by the educational institution? How do applicants who have already become students evaluate their choice of educational institution, the quality of educational service and prospects for their future employment? What is necessary for the formation of demand for educational service? Based on the conducted sociological research, conclusions regarding the choice of educational institution by applicants have been made. The authors’ recommendations to educational institutions to attract applicants and increase their competitiveness in the market of educational services are given.
Generating a Blockchain Smart Contract Application Framework

Blockchain is a new generation technology that allows the central control mechanism or trusted authority to be removed, spreading the encrypted data across all participants in the network in a distributed database structure instead of central trust.The Smart Contract structure, which defines the rules and flow that allow the things we value to operate automatically as determined without the need for an external trigger mechanism, is the core element of this technology.Blockchain has gained popularity with its most famous application, Bitcoin.After Bitcoin became popular, it turned out that Blockchain might have new uses due to the advantage of technology such as security, brokerage, and transparency, and these areas are being investigated.Many big companies have started to invest in this technology in the face of the opportunities brought by Blockchain.HAVELSAN is a largescale software company that studies and adapts new generation technologies.Blockchain technology has become of the new generation technologies that HAVELSAN is interested in due to its impressive advantages.HAVELSAN has a wide range of activities, so the company can develop various Blockchain-based applications depending on these areas.Combining this diversity with the importance of the Smart Contract concept, which can be considered as the basis for most Blockchain applications, it is decided to create a strong Smart Contract framework before starting to build different applications with Blockchain technology.The creation of HAVELSAN Blockchain Smart Contract Framework; which infrastructures are used during the development phase, the problems encountered during development and the structure of the most suitable applications to be created with the framework to be developed will be explained in this article.
Implementasi Manajemen Pembiayaan dalam Pengelolaan Dana Bantuan Operasional Sekolah (BOS) di Madrasah Aliyah Negeri 1 Bitung, Sulawesi Utara

This study aims to describe the implementation of The School Operational Assistance Fund (BOS) funds finance management in MAN 1 Bitung. BOS aims to relieve the burden of society in terms of education fund. Therefore, proper financial management is needed to achieve its purpose. This research uses qualitative approaches using observation, interviews, and documentation as data collection techniques. The results showed that the implementation of BOS finance management in MAN 1 Bitung was realized through the function of planning, implementation, and supervision. Planning involves formulating a budget draft. Then, the implementation stage is done through socialization and disbursement of funds. The final stage is the supervision stage. Through the implementation of this management function, BOS finance management in MAN 1 Bitung positively impacts the education process. Nevertheless, there is a need to coordinate with every element of the madrasah to ensure accountability for BOS funds.
Improving Deep Learning Models via Constraint-Based Domain Knowledge: a Brief Survey

Deep Learning (DL) models proved themselves to perform extremely well on a wide variety of learning tasks, as they can learn useful patterns from large data sets. However, purely data-driven models might struggle when very difficult functions need to be learned or when there is not enough available training data. Fortunately, in many domains prior information can be retrieved and used to boost the performance of DL models. This paper presents a first survey of the approaches devised to integrate domain knowledge, expressed in the form of constraints, in DL learning models to improve their performance, in particular targeting deep neural networks. We identify five (non-mutually exclusive) categories that encompass the main approaches to inject domain knowledge: 1) acting on the features space, 2) modifications to the hypothesis space, 3) data augmentation, 4) regularization schemes, 5) constrained learning.
A black market for upvotes and likes

This article investigates controversial online marketing techniques that involve buying hundreds or even thousands of fake social media items, such as likes on Face- book, Twitter and Instagram followers, Reddit upvotes, mailing list subscriptions, and YouTube subscribers and likes. The findings presented here are based on an analysis of 7,426 “campaigns” posted on the crowdsourcing platform microworkers.com over a 365 day (i.e., year-long) period. These campaigns contained a combined 1,856,316 microtasks with a net budget of USD 208,466.
Menstimulasi Kemampuan Menulis Kata pada Pelajaran Bahasa Indonesia melalui Media Visual berupa Gambar bagi Siswa Kelas II SD Negeri 09 Kepahiang

The lack of students' ability to compose and to write words, became the basis and background of this Classroom Action Research.All of this happens, because the teacher never used any exciting material to teach the students and in the end the lesson became boring and lack of enthusiasm from the students.This research was conducted to stimulate the ability of students to write down the words using Visual Media in the form of Images.This Classroom Action Research was conducted in 2 cycles.This research was conducted in 2 nd year of Public Primary School 09 Kepahiang, with the total of 20 students that consist of 8 male students and 12 Female Students.Data Collecting Technique that used in this research was Observation and Reflection.The collected data was analyzed using Qualitative and Quantitative analyzing technique.The result of this Classroom Action Research showed that by using Visual Media in the form of Images, the class activity became more fun and the students' learning outcome improve dramatically.Based on the results of research, a conclusion can be drawn that the use of Visual Media in the form of Images can improve students' word writing skills
Reachability and Safety Objectives in Markov Decision Processes on Long but Finite Horizons

Abstract We consider discrete-time Markov decision processes in which the decision maker is interested in long but finite horizons. First we consider reachability objective: the decision maker’s goal is to reach a specific target state with the highest possible probability. A strategy is said to overtake another strategy, if it gives a strictly higher probability of reaching the target state on all sufficiently large but finite horizons. We prove that there exists a pure stationary strategy that is not overtaken by any pure strategy nor by any stationary strategy, under some condition on the transition structure and respectively under genericity. A strategy that is not overtaken by any other strategy, called an overtaking optimal strategy, does not always exist. We provide sufficient conditions for its existence. Next we consider safety objective: the decision maker’s goal is to avoid a specific state with the highest possible probability. We argue that the results proven for reachability objective extend to this model.
Development of asset management model using real-time equipment monitoring (RTEM): case study of an industrial company

Globally, the issue of implementing efficient and effective asset management systems has been a challenge for most companies, especially those operating in the oil and gas industry due to the complex nature of their operations. In recent years, with the decline of oil prices, market conditions have become so competitive such that even a few minutes of downtime of equipment could lead to significant loss of revenue. A case study of an Industrial Company is presented, with the goal of assessing its current asset management system. Based on the evaluation of the current asset management system practiced by the Company, it was noted that there are significant gaps in the current practice, and the Company is yet to leverage advanced technological tools in managing its assets. Specifically, the Company does not currently have an appropriate system of tracking and monitoring its assets location, and utilization, despite the fact that the assets move from one location to another in fulfilling customer's needs. A Real-Time Equipment Monitoring system is developed for the industrial company using GPS, Barcodes and RFID technology to provide information relating to assets location, status, condition and maintenance history which led to 30.8% increase in assets utilization. Generally, a benefit analysis carried out shows that the new system will always provide real-time observation data and instrument parameters for maintenance engineers and ultimately company managers for effective decision-making at strategic levels.
Development of Moodle Learning Management System-Based E-Learning Media in Physics Learning

This study is about the development of online learning media or e-learning, which is based on the Moodle Learning Management System (LMS) in physics learning.This study aims at investigating the feasibility, practicality, and effectiveness of e-learning within the learning process.The development model used in this study was the ADDIE model consisting of Analyze, Design, Development, Implementation, and Evaluation.The trial subjects in this study were 13 students of Physics Education Department of Universitas Papua who enrolled in Physics 101 during the second semester of the 2018-2019 academic year.The appropriateness of elearning media was obtained through the feedback sheet filled by seven validators, which consisted of learning media experts and practitioners, whereas, effectiveness and practicality of the e-learning media were obtained through students' responses following the learning process.This study reveals that the developed learning media is within appropriate categories in all its aspects, such as layout, navigation aspect, function aspect, and pedagogical aspect.The students' responses on the utilization of this e-learning media turn out to be effective and practical in each aspect of the assessment.Therefore, Moodle LMS based e-learning media is appropriate to be utilized in physics learning.
When does MAML Work the Best? An Empirical Study on Model-Agnostic Meta-Learning in NLP Applications

Model-Agnostic Meta-Learning (MAML), a model-agnostic meta-learning method, is successfully employed in NLP applications including few-shot text classification and multi-domain low-resource language generation. Many impacting factors, including data quantity, similarity among tasks, and the balance between general language model and task-specific adaptation, can affect the performance of MAML in NLP, but few works have thoroughly studied them. In this paper, we conduct an empirical study to investigate these impacting factors and conclude when MAML works the best based on the experimental results.
Innovative Research on the Improvement of Visual Quality of Data Journalism in China: Visual Language and Interaction Design

Abstract As the last node of data journalism creation, visual design plays a crucial role in the transmission of data information. Exploring the routes to improve the quality of data journalism at the visual language and interaction design, this paper analyzes the works won data journalism awards and produced by well-known media from 2012 to 2019, and discusses the misunderstandings and shortcomings in the current data journalism visualization practice. This paper presents the improvement routes of data mapping, symbolic expression, interaction level, and interactive narration.
Adapting Participatory Design for Romanian Preschoolers Educational Software Development

The Participatory Design (PD) approach cannot be applied to developing software applications for small children (3-5/6 years) without considering the main constraint brought by their age: they cannot be involved in every step of the design.This paper presents our approach in adapting PD for preschoolers in the context of developing educational software that can be used as support for the teaching activities in Romanian kindergartens.We describe and discuss the results of evaluating the obtained software products with preschoolers and their teachers.
Functorial Language Games for Question Answering

We present some categorical investigations into Wittgenstein's language-games, with applications to game-theoretic pragmatics and question-answering in natural language processing.