Reviewerly/exHarmony huggingface dataset:
SISTEM INFORMASI MANAJEMEN ASET MENGGUNAKAN PENDEKATAN MVC DENGAN FRAMEWORK CODEIGNITER DI PT. H-TECH OILFIELD EQUIPMENT

An asset is an important component in a company that is used to support business processes. Of these assets are also obtained production results in the form of a product or service that has a sale value so as to produce a profit. Therefore, the existence of assets within a company becomes very important. In the process of asset maintenance, then the information associated with the assets will be indispensable and must be accessed quickly. Such information may include technical data Specifications historical assets or of the assets. For that we need a computer-based information system that is used to manage data assets of the company. Based on these needs, then made an information system that will be used to manage the assets of the company for asset information can be easily traced when necessary. The information system is made using the PHP programming language with the help of CodeIgniterframework which uses MVC approach. For asset data storage needs, then use MySQL or MariaDB RDBMS based Open Sources, so that the license fee system can be suppressed. The end result of making this system is expected assets owned by the company can be managed properly. So that all information relating to the item can be found quickly when needed.
Europe will push open access forward﻿

In 2016, European Union member states agreed that by 2020 all scientific articles should be open access immediately upon publication. As that deadline approaches, several initiatives are pushing to meet that goal. The newest of these, Plan S, is an agreement among 13 national funders and three charitable foundations, including the Bill and Melinda Gates Foundation, to require grant recipients to publish only in journals that make all content freely accessible. The plan faces criticism. Over 1,500 researchers have signed an open letter voicing concerns, and some funders have chosen to express support for the plan but not sign it. For example, the Swedish Research Council has stated that it needs time to evaluate the Plan S timeline and guidelines. The coalition behind Plan S is looking for more funders to join it in 2019. It is also gathering feedback from the public until Feb. 1. Meanwhile, consortia continue to
Discounted Markov Decision Processes with Constrained Costs: the decomposition approach

In this paper we consider a constrained optimization of discrete time Markov Decision Processes (MDPs) with finite state and action spaces, which accumulate both a reward and costs at each decision epoch. We will study the problem of finding a policy that maximizes the expected total discounted reward subject to the constraints that the expected total discounted costs are not greater than given values. Thus, we will investigate the decomposition method of the state space into the strongly communicating classes for computing an optimal or a nearly optimal stationary policy. The discounted criterion has many applications in several areas such that the Forest Management, the Management of Energy Consumption, the finance, the Communication System (Mobile Networks) and the artificial intelligence.
DEVELOPING CONTENT COMPONENT OF ARGUMENTATIVE WRITING THROUGH GENRE PEDAGOGY: IN PAKISTANI CONTEXT

This paper examines the effectiveness of the Reading to Learn (R2L) approach to teaching argumentative writing skills to undergraduate Pakistani English language learners’ (PELLs) ; as researches (Ilyas, Iqbal, & Fazal, 2015) have found out that PELLs face the problem of integrating perception and lexico-grammar on a given issue to convince readers while writing it. The study experimented with R2L genre pedagogy with a two-group pre and posttest design on a sample of 36 students in each group. The functional analysis of Pretest revealed that PELLs constructed a viewpoint with inappropriate transitivity selection and low lexical density. They ignored nominalization to develop chains of reasoning within the clause. After a four-month intervention, the posttest analysis showed that the performance of the experimental group has significantly improved. Our experimentation and analysis provide a concrete pedagogic assessment of R2L genre pedagogy in the Pakistani context that can help teachers to develop the argumentative writing skills of their students.
Small Order Patterns in Big Time Series: A Practical Guide

The study of order patterns of three equally-spaced values x t , x t + d , x t + 2 d in a time series is a powerful tool. The lag d is changed in a wide range so that the differences of the frequencies of order patterns become autocorrelation functions. Similar to a spectrogram in speech analysis, four ordinal autocorrelation functions are used to visualize big data series, as for instance heart and brain activity over many hours. The method applies to real data without preprocessing, and outliers and missing data do not matter. On the theoretical side, we study the properties of order correlation functions and show that the four autocorrelation functions are orthogonal in a certain sense. An analysis of variance of a modified permutation entropy can be performed with four variance components associated with the functions.
Once again, physicists ask, how magnetic is the muon?

First new result in 15 years could signal new particles.
Case Study: Semaphores

Mutex and semaphore contention is one of the most elusive kinds of contention you can come across as except for extreme situations, you will not directly notice any issues. Instead, the contention tends to materialize as an overall added latency and throughput reduction that can be hard to put your finger on. Then out of the blue, you may have crossed a load threshold, and the contention causes your server to come to a grinding halt.
Blockchain Analytics for Intraday Financial Risk Modeling

Blockchain offers the opportunity to use the transaction graph for financial governance, yet properties of this graph are understudied. One key question in this direction is the extent to which the transaction graph can serve as an early-warning indicator for large financial losses. In this article, we demonstrate the impact of extreme transaction graph activity on the intraday volatility of the Bitcoin prices series. Specifically, we identify certain sub-graphs ('chainlets') that exhibit predictive influence on Bitcoin price and volatility and characterize the types of chainlets that signify extreme losses. Using bars ranging from 15 minutes up to a day, we fit GARCH models with and without the extreme chainlets and show that the former exhibit superior Value-at-Risk backtesting performance.
Interpretation of Packaging Design and Generic Drug Labels Production of PT Kimia Farma (Study from an Art Pragmatic Perspective)

This study discusses the interpretation of the message or meaning conveyed in the packaging design and generic drug labels produced by PT Kimia Farma. PT Kimia Farma is one of the leading companies in Indonesia which still exists to produce pharmaceuticals. This study aims to help the user community quickly understand the message or meaning contained in the drug packaging or label. The transmission of meaning conveyed is generally expressed in written form in the form of a sentence containing, among other things, instructions for drug use and company identity. Besides, it also takes the form of packaging design, for example, cylindrical, cube, etc. The conditions in question function as a place to protect the contents, namely that the drug is kept hygienic. The importance of interpreting the message or meaning from the linguistic side so that the user community does not misinterpret its usage. Because if something goes wrong, it will have a fatal impact on the health side. Moreover, if it is related to a doctor's written code of ethics, for example, the message conveyed is not easy to grasp. The problem raised in this study is how the easiest way to interpret the message contained in the drug's packaging and label. The study was carried out using a qualitative paradigm, which is a single, embedded, descriptive case study. Data is compiled from document/archive sources or libraries. The data validity used data triangulation. The data were analyzed using the pragmatic analysis model. The findings indicate that the messages conveyed in the packaging and drug labels are disclosed in writing, for example, technical instructions for drug storage, deadlines for taking medication, and prohibitions. Even though taking medicine at the pharmacy, the officer had delivered a message in a list manner, helping to interpret the news from a linguistic side in a pragmatic way was very useful. In this case, diagnosing the message or meaning is not just translating it vulgarly, but practical linguistic studies of art are related to its context.
Towards Adversarial Robustness of Bayesian Neural Network through Hierarchical Variational Inference

Recent works have applied Bayesian Neural Network (BNN) to adversarial training, and shown the improvement of adversarial robustness via the BNN's strength of stochastic gradient defense. However, we have found that in general, the BNN loses its stochasticity after its training with the BNN's posterior. As a result, the lack of the stochasticity leads to weak regularization effect to the BNN, which increases KL divergence in ELBO from variational inference. In this paper, we propose an enhanced Bayesian regularizer through hierarchical variational inference in order to boost adversarial robustness against gradient-based attack. Furthermore, we also prove that the proposed method allows the BNN's stochasticity to be elevated with the reduced KL divergence. Exhaustive experiment results demonstrate the effectiveness of the proposed method by showing the improvement of adversarial robustness, compared with adversarial training (Madry et al., 2018) and adversarial-BNN (Liu et al., 2019) under PGD attack and EOT-PGD attack to the L∞ perturbation on CIFAR-10/100, STL-10, and Tiny-ImageNet.
A Hybrid Approach for Page Relevance Computation

Internet became very effective tool to exchange the information on wide basis. As information on the web keeps on changing, it is becoming an important requirement to find a system which retrieves the most relevant and highly worthy pages and find out changes in minimum time.Focused crawlers aims to find out only that portion of the web which is related to some specific topic, and offer a prospective solution to retrieve relevant pages.In this paper, We proposed a method to compute page relevance using page weight. Also a hybrid approach for computation of topic specific weight table is also discussed.
QoE-aware Bandwidth Allocation for Multiple Video Streaming Players over HTTP and SDN

For many years, the most popular technique for Internet video streaming is hypertext transfer protocol-based adaptive streaming, known as HAS (HTTP Adaptive Streaming).However, a seamless viewing experience can not be just simply guaranteed by HAS only.In the management network, the adaptation of HAS copes with a huge challenge since clientdriven schemes lead to unfair share of available bandwidth when multiple players request adaptive bitrates (i.e bandwidth) through a bottleneck network link.Each client's requesting to maximize its needed bandwidth leads to the competition of network resources.This causes great QoE (Quality of Experience) reduction in terms of main metrics for each player: fairness, efficiency, and stability.In this paper, we propose an integration scheme of bitrate adaptation and Software Defined Networking-based resource allocation that can improve the QoE of competing clients.Our experiments show that the proposed scheme increases at least 20% up to 124% in terms of QoE scores compared with some existing methods as well as gains smoother viewing experience than the solutions of the traditional Internet.
Improvement of the efficiency of cognitive activities of trainers when studying technical disciplines through technologies of problem training

Improvement of the efficiency of cognitive activities of trainers when studying technical disciplines through technologies of problem training
SISTEM PENGELOLAAN KENDARAAN DINAS DI PEMERINTAH KOTA SALATIGA

The optimal management of regional property has become a basic requirement for local governments in realizing good governance. Official vehicles as one part of regional property have a significant function. However, the process of managing official vehicles in regional organizations of Salatiga government is still not optimal. For example, the frequency of vehicle maintenance schedules are missed and vehicle tax payments are due. The change of official vehicle users also often occurs and it will be a problem if the process is not recorded properly. This study aims to design an applications in supporting regional organizations at Salatiga government for managing data and presenting information related to official vehicles. This study used the Linear Sequential Model / Waterfall Model. The data collection covered observation, interviews and literature study. The application wasmade in the form of a desktop application using the Node.js platform and it is based on javascript and utilizes the electron framework. The database used SQLite. Analysis and design of the system used a structured method through the stages of making normalization, relations between tables, entity relationship diagrams, data dictionaries, data flow diagrams, flowcharts, and interface design. The resulting application is tested using the blackbox testing method. The analysis of test results shows that the application is functioning normally according to the expected results. The main function of managing data on the use and maintenance of official vehicles has been successful through all the test scenarios conducted.
Perancangan dan Implementasi Website Pariwisata di Desa Sembulang dengan Metode Extreme Programming

Geographical information system or GIS is a geographic system that has been widely used, especially by tourists or tourists. In this study, GIS was used to map Sembulang village with the aim of reaching tourist attractions in Sembulang village to tourists, both from within the country and from abroad. It is hoped that with a geographic information system that can attract visitors to the tourist attractions of Sembulang village. This system is built using the programming language HTML, Javascript, and CSS and uses several assistance applications such as XAMPP and Sublime Text Editor.
CORPORATE CRIMINAL LAW, ARTIFICIAL INTELLIGENCE AND BIG DATA: THE HUAWEI CASE AND ITS IMPLICATIONS FOR GLOBAL SOCIETY

The impact of artificial intelligence can be significant in determining corporate risks. In turn, Big Data can provide relevant information on events that impact the business world as concrete dangers. This should be done by evaluating endogenous and exogenous variables that can be interpreted together. However, this approach requires the development of additional strategies in the company that are aimed at education, training and updating technological notions and digital innovation tools.  This is because Big Data and Artificial Intelligence complement each other and can represent a potential change in the parameters of cyber criminal law.The Huawei case is a representation of the industrial revolution, economic and data-driven digital intelligence revolution, reflecting the repercussions of the actions of a multinational company that allegedly violated the regulations of a third country, in this case the United States. As it is a major corporation that provides services in the telecommunications devices and equipment market, its operation broadly affects the global economy and the digital society. The criminal process against the company by the United States may affect the operational, reputational and commercial capacity of the company in transnational relationships for technological and digital exchange on a global scale
The Relationship Between Patterns of Care and Level of Emotional Intelligence Among Pre-School Children

Psychologists Salovy from Harvard University and Mayer from the University of New Hampshire reveal that emotional intelligence is an emotional quality that is important for a successful life. These qualities include empathy, expressing and understanding feelings, controlling anger, independence, ability to adapt, to be liked, ability to solve interpersonal problems, perseverance, solidarity, friendliness and respect. Factors that can affect emotional intelligence include psychological factors, emotional training factors and family education factors. The purpose of this study was to determine the relationship between parenting style and the level of emotional intelligence of preschool children. The research design used was cross-sectional, the research was carried out at TK Kemala Bhayangkari 48 Tulungagung,The results showed that respondents who received authoritative care were 16 children (53.3%) who all had emotional intelligence, including in the smart category. Meanwhile, none of the children who received authoritative care were in the less intelligent category. The results of the Chi-Square statistical test showed that p = 0.000 <α = 0.05, which means that there is a relationship between parenting styles and the level of emotional intelligence of preschool children.It is concluded that different parenting styles will produce children with different levels of emotional intelligence. The better the parenting method, the better the level of intelligence of a child. Recommendations for future researchers are expected to further investigate the factors that can influence the individual characteristics of parents and the level of emotional intelligence of preschool children.
Artificial Intelligence, Neoliberalism and Human Rights

Discrimination, bias, inequality, and inequity, are terms that are all too commonly associated with education for those obscured in the margins and excluded from the main. Herein, we attempt to chorus the voices that have remained in the shadowy discourses of inclusive education. Further, we fuse diverse sociological perspectives and examine points of friction, murmuration, and interplay. Through this, we endeavor to move beyond empty rhetoric and what has become the canonical assumptions of inclusive education. Instead, we turn to considerations of multiplicity; in doing so we take up arms at the intersections of the impact of neoliberalism and artificial intelligence, poverty and regional education, and finally the utilization of camouflage to hide the social realities of segregation. Through these narrative junctures, we find solace in the capacity to call out exclusion, irregularity, and oppression and complicate the underside of inclusion which scratches at common-sensical notions that inclusive education is a Right, right?
Distributed Data Protection and Liability on Blockchains

Blockchains and the GDPR pursue similar objectives where they seek to grant users greater control over their personal data. While the latter pursues this goal by imposing duties of care to centralised controllers and collectors of data, blockchains go a step beyond by trying to eliminate these stakeholders and the need to trust them. Nevertheless, the rules set out by the GDPR apply whenever personal data are at stake, and various actors of the blockchain ecosystem risk liability for controlling of processing data in violation of privacy requirements. A possible solution is to re-contextualise the concepts of data controlling and responsibility, as framed by the GDPR, in light of blockchains’ enhanced individual autonomy. In this paper, we set the framework for a further inquiry on the role of users as both data subjects and data controllers of distributed ledgers.
Framework for Assessing Maturity of Future Manufacturing System

In an environment transformed by smart factories, measuring the current level of the manufacturing system, deriving improvement targets and tasks and increasing the level of manufacturing competitiveness become the basic activities of the company. However, research on the component analysis and maturity assessment to ensure the future competitiveness of the company is in progress and in the early stages. This study analyzed the existing research on various models, development process, and framework for manufacturing system. In addition, we designed a structural model by deriving the components of future manufacturing system through smart factory related maturity assessment studies. We designed a meta-model that includes an assesment model and a transformation model, and derived the framework development process to propose an integrated framework for the maturity assessment of the future manufacturing system. We verified it by applying it into an actual evaluation project of smart factory.
Project Based Learning Methodology: An Effective Way of learning Software Engineering through Database Design and Web Technology Project

Nowadays, Project-based learning is an integral part of many professional courses in Engineering.Projectbased learning is a student-centric approach in which students learn about a course by working in groups to solve an open-ended real world problem.In our opinion, it takes students near to the real world at a very early stage.For students, it acts as a tool to learn concepts and principles, to adapt to the evolving ICT industrial requirements and challenges.The objective here is to convey our systematic teaching and learning method, based on Project-based learning, to effectively learn the principles and practices of Software Engineering.Also, it prepares students how to apply these theoretical concepts to solve the real world problems by working in a team.For more than 10 years we are conducting this activity very rigorously for Third Year Computer Engineering students.This activity incorporates applying theory of Software Engineering to develop experiential learning by developing a mini-project using Database and Web Technology.Our 7point method for development of mini-project has continuous Assessment through critical reviews and presentations by students.We conducted survey for all batches and took their feedback to understand the role of Project Based Learning in their Professional Career.Feedback of these students helps us to update our methodology and/or course contents.Applying Database technology and getting acquainted with development of user interface is bit easy for students but applying the Software Development Life Cycle [3] learnt in Software Engineering is quite challenging.There are many skills they learn and acquire while developing mini-project like questions to be asked during field work, design strategy and analysis through modelling, teamwork[4], time management, communication skills and many more which takes them a step closer and works as a basic building block for their growth as a software professional.Our survey questionnaire gives insight of all and acts as a measuring tool.This paper addresses our 7-point method, design, our process of evaluation and challenges faced by the students and faculty during this process with the help of representative projects.
USAGE OF ARTIFICIAL NEURAL NETWORKS IN DATA CLASSIFICATION

Data classification is broadly defined as the process of organizing data by respective categories so that it can be used and protected more efficiently.Data classification is performed for different purposes, one of the most common is for preserving data privacy.Data classification often includes a number of attributes, determining the type of data, confidentiality, and integrity.Neural networks help solve different problems.They are very good at data classification problems, they can classify any data with arbitrary precision.