Reviewerly/exHarmony huggingface dataset:
Analytical Comparison of Cloud Data Centre Services and Cost

Abstract Comparing with the traditional data centre, cloud computing makes it easier for enterprises to scale their services and lowers the cost of access for smaller companies. The cost comparison between cloud computing and the old-style data centre is an important issue of concern. In this paper, the cost roles traditional cloud data centre and server room are settled up, the performance of the data centre and cloud computing were tested based on the compared with the data centre with low workload intensity strength. More than a few data centre have a primary backup of data and servers. The cloud data centre provider like Amazon, Google Facebook data centre are called Availability zones. The availability zones are a within the same region, distinct colocation centre is connected to Virtual Private Cloud network. This research discovering new network architectures for the data centre. In this paper, we considerate the among different data centre charges and network architectures. the comparison on cost using current and predicted trends in data centre cost and power consumption.
A Study on the Aspect of Hedges in English TV News and Korean Translations

This study aims to investigate hedges used in English TV news and their Korean translations. Forty TV news articles (twenty in English and their twenty Korean translations) about nuclear facilities of North Korea were collected for this study, analyzed and compared with the correspondence list of hedge expressions in English and Korean. The result shows that most of the hedges used in both texts are about the speaker’s responsibility for the contents of propositions. Next, hedges related with the contents of propositions are examined the second most. Lastly, small numbers of hedges concerned with the relationship between the speaker and hearer are used. A few discrepancies in hedges in English texts and Korean translations are found. In learning English with news texts, it is recommended that teachers should teach such discrepancies in hedges in both texts to learners. Studies on other linguistic strategies (e.g., booster, attitude marker) or other genres (e.g., newspaper, magazine) are suggested for future research.
PENGEMBANGAN KETRAMPILAN BAHASA ASING BAGI SISWA SMA IMMANUEL BATAM DALAM MENYONGSONG ERA REVOLUSI INDUSTRI 4.0

The purpose of this community service program is to equip and increase student interest in learning English and Mandarin through providing techniques and tips that make it easier for students to learn foreign languages at SMA Immanuel Batam. The method of implementation used is conducting webinars using the Zoom application and distributing E-Books as learning materials to make it easier for students to learn the two languages. This program is implemented for one semester and the results show that students who actively participate in activities are more motivated in learning foreign languages so that their competence increases.
Machine Learning Techniques as Mechanisms for Data Protection and Privacy

The exponential use of the Internet in the world has changed the way that data are collected, exchanged, and manipulated. Processing speeds, information volumes, and content relevance have changed rapidly to unimaginable levels. This is associated with the interest in creating personalized services based on the information available. Different organizations have data about people, representing a critical element, and it is estimated that up to 80% of all data stored in organizations can be classified as big data. The data stored by organizations usually comes from multiple sources (devices, people, organizations, among others), and these sources become the producers of the data. These data can be published or shared with other organizations or individuals, so the recipients of these publications become the consumers of the information. This research exposes problems in measuring the usefulness of data and relates them to the preservation of privacy in publishing. Machine learning models are developed to determine the risk of predicting sensitive attributes and as a means of verifying the utility of the data.
Profile Summarization From Semantic Data Using Deep Neural Network Model

By querying a Database, the results are often triples. It is a time consuming job to understand the triples and identify the relationship between the m and also the information contained in it. So think of an automated system that could convert these triples into English language. Wont it be a boon to this hustling world?? That is just the thing proposed in this paper. Summarization plays a crucial role in this hectic world. Everyone is busy and hence no time to spend to read long paragraphs and understands their meaning. Automatic text summarization is a challenging task that involves lot of steps. One of the hurdles is to understand the meaning of the text and then process it. So in this work, semantic data in the form of RDF Triples is being given and using deep learning approaches, a concise and coherent summary is being generated. This work primarily focuses in the domain of profile summarization. A study about systems that perform RDF to natural language conversion is been done and inferred information that models to develop the proposed system. The limitation of such models is that only intra triple relationship is conserved. And this limitation is solved in the proposed model by using a knowledge graph constructed from RDF triples.
The Selection of Economic Horticulture for Suitable Planting in Ubon Ratchathani Province by Data Mining Techniques

The objectives of this research were to create models and develop a program that selects suitable economic horticulture for the cultivated areas in Ubon Ratchathani Province using 2 - steps data mining techniques : K - means clustering technique and Decision tree classification technique . The secondary data in 2015 - 2017 were used in this research . The input variables were soil data, economic horticultural data, climate data, and area . The class variable was the 14 types of economic horticulture . The result of the K - means clustering found that Ubon Ratchathani Province was classified in the third cluster with a total of 207 districts in 15 provinces . The results of the decision tree classifications found that 1 ) the suitable economic horticulture for planting in all districts of Ubon Ratchathani Province were rambutan, rubber, oil palm, and citrus with an accuracy of 75 . 77 % , 71 . 42 % , 69 . 23 % , and 58 . 84 % , respectively . 2 ) The suitable economic horticultures for planting in some districts of Ubon Ratchathani Province were mangosteen, lychee, tangerine, durian, longan with an accuracy of 87 . 37 % , 87 . 37 % , 86 . 24 % , 85 . 73 % , and 85 . 23 % respectively . When the model of horticultural selection was used to develop a program in web application . The satisfied level of a sample of the farmer to a program that selects suitable economic horticulture for the cultivated areas in Ubon Ratchathani Province was high level . Keywords : data mining ; clustering;  classification
The Evolution of Currency: Cash to Cryptos to Sovereign Digital Currencies

In 2009, Bitcoin created a world-first decentralised alternative currency that has spawned over 1,700 imitations by private parties. In 2018, governments finally joined the race, as Venezuela issued a world-first sovereign digital currency. Major economies like Canada, China, Singapore and the UK are all developing their own versions. These new versions differ significantly from Bitcoin and among themselves, creating the potential to flood the global financial system with a myriad of new digital currencies. Existing taxonomies of currency struggle with the speed of change (frequently due to inadequate understanding of the underlying technology) and, as a result, remain incomplete and filled with confusing and conflicting vocabulary (with terms like ‘virtual currencies’, ‘digital currencies’, ‘cryptocurrencies’ frequently being used to refer to the same thing). This article resolves this problem. First, it analyses existing forms of currency based on their functional characteristics and provides a comprehensive taxonomy. Second, it integrates the likely forms of upcoming sovereign digital currencies into this taxonomy and outlines the corresponding challenges. At the moment, no major economy seems keen to issue a sovereign digital currency, but if one does, others will, for good reasons, respond in kind and the ground will be laid for a sovereign digital currency battle royale.
Semantic Segmentation Based on Deeplabv3+ With Fractional-Order Image Enhancement Convolution Kernel

Deeplabv3+ [11] proposed by Google Inc. is a Semantic Segmentation model after deeplabv3 [10]. Deeplabv3+, which creatively added the decoder structure with the previous version as an encoder part to enhance the ability of the model to recover spatial resolution and location information, reached the state-of-the-art 89% MIoU on the PASCAL VOC2012 dataset. However, the model does not perform well in achieving good results on the image edge segmentation, due to the structures of the down-sampling and spatial convolution, lots of detail information were lost in the training process. In this paper, a semantic segmentation method that combined a deeplabv3+ model with the fractional-order image enhancement convolution kernel is proposed. In order to optimize the edges of segmentation results, the fractional-order image enhancement mask is used as convolution kernel to enhance the edge feature of the input images. Our method in this paper shows better performance than the original deeplabv3+ model on the image edge segmentation, and also maintains more than 89% MIoU on the PASCAL VOC2012 dataset.
Cybercrime in Automotive Security in the 21th Century

. Intelligent transportation systems introduce smart technology to civil transportation infrastructure. Modern services depend on the use of information technology systems. Cybersecurity plays an important role in the ongoing development of information technology. Enhancing cybersecurity and protecting critical information infrastructures are essential to each national security. Nowadays, vehicles are equipped with electronic security systems that automatically call the emergency service operator in case of an accident. This safety system combines different technology in order to ensure vehicle safety. When you are unconscious, the system informs the rescuers where the accident happened. They arrive at the scene of the accident within a few minutes. The introduction of this system in vehicles results from Regulation (EU) 2015/758 of the European Parliament and of the Council of 29 April 2015 on type-approval requirements for the deployment of the 112 on-board eCall system and amending Directive 2007/46/EC. Nevertheless, there is concern that this could expose connected cars with their passengers to potential risks from online threats. Scientific development for the security of our vehicles has also raised the possibility of misuse of vehicle data. It is seen that e-threats have become the leading threats in the further deployment of e-services in the society of the 21st century.
More Best Practices

PIM is all about the benefits that come from incorporating best practices into your development process. Generally, the more best practices you follow, the easier your life is, and the better your chance of delivering your project on schedule. To that end, this chapter describes some best practices that will make your software development life easier and reduce the headaches along the way. I realize that there will be situations and technical considerations that may not allow you to follow these best practices, but do not ignore them.
IMPROVING STUDENTS’ READING COMPREHENSION IN NARRATIVE TEXT OF VIII GRADE AT SMPN 3 TOLITOLI THROUGH SELF-QUESTIONING STRATEGY

The objective of the research is to find out whether the use of self-questioning strategy improve the students’ reading comprehension in narrative text.The design of this research is experimental research. The population of this researchis the eighth grade students of SMP Negeri 3 Tolitoli in the academic year of 2016/2017. The number of the subjects is 35 students. The data areobtain by administering reading test to the VIII B. The research is started by giving pre-test, treatments,and post-test. The data of the test areanalyze by using t-test formula to know the difference of the students’comprehension in reading narrative text. In the pre-test, the mean score of the experimental research is 49.34. The mean score of post-test of the experimental research is 83.20. The result of the t-test differenceis 11.848and t-table is2.032. It means that t-value is higherthan t-table (11.848>2.032). The calculation reveal that the hypothesis about asignificant difference on reading comprehension between students who arethrough narrative text by using Self-Questioning strategy.Based on the research conduct, it is  prove that the use of Self-Questioning strategy is effective as a strategy to improve students’ Reading Comprehension In Narrative Text of VIII Grade At SMPN 3 Tolitoli. Key Words : Improve, Reading Comprehension,Self-Questioning strategy,Narrative text,
A Contrastive Study of English and Korean Argument Structure Constructions

This paper aims to propose a contrastive analysis of English and Korean argument structure constructions (ASCs) in the framework of Construction Grammar. Although Construction Grammar is best known for its thesis that ASCs can exist independently of argument taking verbs in English, it has yet to be investigated whether the equivalent patterns of argument structures or ASCs are available in Korean. In order to find the equivalent patterns, the present paper examined 7 types of English ASCs (of Goldberg 1995, 2019) and their Korean counterparts. As a result, it turned out that Korean equivalents of English examples of ASCs with coercion effects do not involve coercion effects. However, this does not indicate that Korean ASCs can not exist independently of argument taking verbs because it is observed that transitive construction exceptionally produces coercion effects, and case marking postpositions and verb endings are playing a pivotal role in the emergence of ASCs and other constructions in Korean.
「残る·残す」と「남다·남기다」の日韓対照研究

This paper presents an investigation into the Japanese verbs ‘nokoru (残る)·nokosu (残す)’ and their Korean counterparts ‘namda (남다)·namgida (남기다)’ from the perspective of contrastive linguistics. The study provides three major results that have not been stated in previous studies:ⅰ) Basically, intransitive verbs ‘nokoru (残る) vs namda (남다)’ and transitive verbs ‘nokosu (残す) vs namgida (남기다)’ make two verb pairs that share many common features in a semantic way. They are in contrast to the pair ‘kiru (切る) vs jaleuda (자르다)’ that have more differences than similarities between them.ⅱ) ‘sal-a namda (살아 남다)’ was analyzed as a type with an intervening element and distinguished from ‘~nokoru (残る)’ that belongs to the type of no intervening elements like ‘iki-nokoru (生き残る)’. This approach offers some properexplanations about differences such as the separation of a boundary between them.ⅲ) ‘~nokosu (残す)’ belongs to the type of no intervening elements that has three uses according to 1) whether the act of V1 is complete, 2) whether the act of V1 is suspended or did not occur at all, and 3) whether the survival of an outcome is visible or not. Korean translations corresponding to each of these uses are realized differently.
Highly-Performed Fuzzily-logicized Edge Detecting Algorithm for Noisy Handwritings

The main targets for using the edge detection techniques in image processing are to reduce the number of features and find the edge of image based-contents. In this paper, comparisons have been demonstrated between classical methods (Canny, Sobel, Roberts, and Prewitt) and Fuzzy Logic Technique to detect the edges of different samples of image's contents and patterns. These methods are tested to detect edges of images that are corrupted with different types of noise such as (Gaussian, and Salt and pepper). The performance indices are mean square error and peak signal to noise ratio (MSE and PSNR). Finally, experimental results show that the proposed Fuzzy rules and membership function provide better results for both noisy and noise-free images.
Hyperspectral Image Restoration via Multi-mode and Double-weighted  Tensor Nuclear Norm Minimization

Tensor nuclear norm (TNN) induced by tensor singular value decomposition plays an important role in hyperspectral image (HSI) restoration tasks. In this letter, we first consider three inconspicuous but crucial phenomenons in TNN. In the Fourier transform domain of HSIs, different frequency components contain different information; different singular values of each frequency component also represent different information. The two physical phenomenons lie not only in the spectral dimension but also in the spatial dimensions. Then, to improve the capability and flexibility of TNN for HSI restoration, we propose a multi-mode and double-weighted TNN based on the above three crucial phenomenons. It can adaptively shrink the frequency components and singular values according to their physical meanings in all modes of HSIs. In the framework of the alternating direction method of multipliers, we design an effective alternating iterative strategy to optimize our proposed model. Restoration experiments on both synthetic and real HSI datasets demonstrate their superiority against related methods.
BCSS: Stata module to create graphs to show how baseline data (prospective or retrospective) affect sample size for a cluster randomised trial

bcss displays graphs examining the impact of varying the amount of prospective/retrospective baseline data collection on the number of clusters required in a cluster randomised trial with different cluster autocorrelation and intra-cluster correlation values.
Affordances of decentralised technologies for commons-based governance of shared technical infrastructure

In this article I will illustrate affordances of decentralised technologies in the context of commons governance. My aim is to summarise the conversation around the lecture “When Ostrom Meets Blockchain: Exploring the Potentials of Blockchain for Commons Governance” I gave in the Mereologies Open Seminar organised by The Bartlett School of Architecture at University College London on 25th April 2019. I will also extend the conversation by providing a concrete example of such affordances in the context of a community network.
Effects of ICT on Teaching and Learning: A Review of Related Literature

The advent of ICT has made monumental changes in the world presently. This digital phenomenon has had effect in every facet of human life or endeavor. The introduction of ICT in education helped to improve the quality of education at the point where teaching and learning eventually became an engaging active process related to real life. The present study intends to collate the findings from a review of array of available literature related to the effects of ICT on education. The 21st century teaching and learning skills emphasize the need to transform the conventional teacher-centered pedagogy to more learner-centered methodology. Active and collaborative learning conditions facilitated by ICT helps to develop a knowledge-centered student community. This research work gives an insight into the use of ICT in the field of education, focusing on its impact on teaching learning process, quality, and accessibility of education, motivating learners, learning environment and students’ academic performance.
Gandhi’s Contribution to Education

Mahatma Gandhiji was an extremely open-minded seeker of truth. This quality gives Gandhiji a unique dimension which can attract the new generation. Education is for life, life in its entire and then education through life. Gandhiji philosophy of non-violence has great relevance in current scenario.Such philosophy of life helped him in developing his philosophy of Education which can be the true source of inspiration for the present system of education. Gandhiji’s Basic Principles of Education includes: i)From 7 to 14 years of age, education of each child should be free, compulsory and universal. ii)The medium of instruction should be mother-tongue. iii) Mere literacy cannot be equated with education. Education should employ some craft as a medium of education so that the child gains economic self - reliance for his life. iv) Education should develop human values in the child. v)Education should create useful, responsible and dynamic citizens. By education all the hidden powers of child should develop according to the community of which he is an integral part. vi)Education should achieve the harmonious development of child's body, mind, heart and soul. The inspiration of Mahatma Gandhi, we have adopted Basic Education as the pattern of national education. The distinctive feature of education that it makes productive work is the main basis of the whole educative process. Gandhiji thought that education should be provided to mothers, and they could provide education to children effectively. He stressed upon the education of women, for the development of nation depends upon women. Education is vital for the effectiveness of both strategies. For this to happen, education has to go beyond the warehousing of information to a celebration of awareness, which is best facilitated through education for peace. Gandhiji by sponsoring the New Education made the Indian educational system.
지아친토 셀시의 과도기적 단음 음악: ≪네 개의 트럼펫곡≫ (1956) 분석

The purpose of this paper is to regard the Giacinto Scelsi’s Quattro Pezzi per Trumpet as a gradual process to lead a single-note style in the final movement, and is to suggest analytical tools that might fit in and make one fully understand the complexity of Scelsi’s achievement. Scelsi realized and systematized that a single note might serve ample material for musical composition, an idea that was first suggested by Rudolf Steiner, and composer Dame Rudhyar in 1920s. Scelsi believed that real music has to focus on casual forces that a single note itself is able to release rather than to focus on a interrelation between pitches. The casual forces might derive from timbre, dynamics, micro-tones, articulation, and etc. Being regarded as a transitional single-note work, his Quatter Pezzi per Trumpet demonstrates the gradual process, which are expressed through reducing the number of pitches and pitch ranges, revealing the central pitch, and relating the micro tone to the central pitch. This paper suggests that the grid graph may become effective as an analytical tool, in which visualizing pitch distribution and pitch centricity in each single note work.
On the Effectiveness of Deep Ensembles for Small Data Tasks

Deep neural networks represent the gold standard for image classification. However, they usually need large amounts of data to reach superior performance. In this work, we focus on image classification problems with a few labeled examples per class and improve sample efficiency in the low data regime by using an ensemble of relatively small deep networks. For the first time, our work broadly studies the existing concept of neural ensembling in small data domains, through an extensive validation using popular datasets and architectures. We show that deep ensembling is a simple yet effective technique that outperforms current state-of-the-art approaches for learning from small datasets. We compare different ensemble configurations to their deeper and wider competitors given a total fixed computational budget and provide empirical evidence of their advantage. Furthermore, we investigate the effectiveness of different losses and show that their choice should be made considering different factors.