Reviewerly/exHarmony huggingface dataset:
Internet of Thing Based Automatic Temperature and Humidity Regulation Model for Oyster Mushroom Cultivation

Digital communication technology between machine-to-machine grew quickly compared to the past years. Due to recent breakthroughs, it is easy to set up small devices which are capable to talk with each other perform automated tasks. Because of this reason, most of Internet of Things (IoT) can be used as a monitoring and automatic regulation model for any sector, namely agriculture. IoT can help the farmers, especially oyster mushroom cultivation to ensure proper mushrooms' growth. Oyster mushrooms require strict conditions to grow properly before harvest season starts. These strict requirements such as temperature and humidity are hard to monitor and regulate hourly, and farmers must check the cultivation one-by-one manually. Hence, IoT-based automatic temperature and humidity regulation model is expected to help farmers to maintain the current temperature and humidity hourly or even live situation of their cultivation. The purpose of this research is to develop an IoT-based automatic temperature and humidity regulation model to adjust oyster mushroom cultivations’ temperature and humidity using DHT22 digital sensor with a built-in tool such as pump and fan without human intervention.
Scientometrics dimensions of world bitcoin research: A study based on scopus database

Since 2009, there has been creating enthusiasm for bitcoin scientific research from different fields, which incorporate software engineering and designing, financial matters, trade and money, law, and regulatory. The reason for this paper is to evaluate bitcoin writing dependent on the structures and systems of science, as an essential advance inside the investigations of this new marvel. Dissecting the developing logical writing on bitcoin distributed somewhere in the range of 2009 and 2019, we outfitted useful insights on academic research on this subject concerning publication year, type and category, Highly prolific authors, major journals and citations. Scopus database was used for the gathering 3188 documents. Our study provides a knowledge area map that identifies and evaluates the links between author's and countries’ distribution, the conceptual structure of the sphere, the structure, and connections of most cited papers and journals. Resuming our findings, we note a concentration of the interest in some keywords (bitcoin, cryptocurrency, blockchain) and on a few influential authors.
Link Prediction using Network Embedding based on Global Similarity

Background: The link prediction issue is one of the most widely used problems in complex network analysis. Link prediction requires knowing the background of previous link connections and combining them with available information. The link prediction local approaches with node structure objectives are fast in case of speed but are not accurate enough. On the other hand, the global link prediction methods identify all path structures in a network and can determine the similarity degree between graph-extracted entities with high accuracy but are time-consuming instead. Most existing algorithms are only using one type of feature (global or local) to represent data, which not well described due to the large scale and heterogeneity of complex networks. Methods: In this paper, a new method presented for Link Prediction using node embedding due to the high dimensions of real-world networks. The proposed method extracts a smaller model of the input network by getting help from the deep neural network and combining global and local nodes in a way to preserve the network's information and features to the desired extent. First, the feature vector is being extracted by an encoder-decoder for each node, which is a suitable tool for modeling complex nonlinear phenomena. Secondly, both global and local information concurrently used to improve the loss function. More obvious, the clustering similarity threshold considered as the local criterion and the transitive node similarity measure used to exploit the global features. To the end, the accuracy of the link prediction algorithm increased by designing the optimization operation accurately. Results: The proposed method applied to 4 datasets named Cora, Wikipedia, Blog catalog, Drug-drug-interaction, and the results are compared with laplacian, Node2vec, and GAE methods. Experimental results show an average accuracy achievement of 0.620, 0.723, 0.875, and 0.845 on the mentioned datasets, and confirm that the link prediction can effectively improve the prediction performance using network embedding based on global similarity.======================================================================================================Copyrights©2020 The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers.======================================================================================================
Educación mediada por las tecnologías: un desafío ante la coyuntura del Covid-19

The purpose of this argumentative essay is to reflect on the uncertainty faced by the human being in the educational sector, that requires the transition from the modality of face-to-face education to another based on technology, in the face of the covid-19 pandemic and, from this, reveal the challenges for the implementation of technology-mediated education, in a turbulent environment, using references that help us understand the phenomenon linked to education and face the changes that emerge to guarantee continuity. It is developed under an interpretive approach from which two significances are revealed for the human being in the days of COVID-19: the shift from face-to-face education to that sustained by education technology.The argumentative study led to the construction of challenges for the implementation of technology-based education. It concludes with thoughtful ideas that reaffirm the need to recognize and resignify that human being who must go through changes in the educational model; that implies assuming new understandings in decision-making in a turbulent environment, full of uncertainty such as the one that is happening in today’s world.
3D Reconstruction Based on Style Transfer Data Augmentation

Recently, various technologies using PointCloud and Deep Neural Network (DNN) have been actively researched. However, there is a disadvantage that the collecting PointCloud data from real object with special sensors such as depth sensor is time consuming task. To deal with this problem, we focus on 3D reconstruction from a single image. Conventional methods construct PointCloud from a single image which includes mask information. Therefore, it is difficult to construct a PointCloud from an image without mask information. To remove the requirement of the additional information such as mask for input image, we propose data augmentation based on style transfer for 3D reconstruction. It is known that DNN using style transformed image can learn a shape feature. By using the transformed images, the DNN can learn object shapes with various backgrounds and textures and can obtain shape features even from the images with cluttered background. From the experimental results, we confirmed that our proposed method could construct 3D object shape with PointCloud while keeping shape information without additional information.
IEEE Paper Based on E-Novels

Nowadays, the net plays an important role in people’s life. In the process of the improvement of the public’s living standards, public’s demands of the life’s quality and efficiency is higher, the traditional bookstores inconvenience gradually emerged, and the online bookstore has gradually been used in public. The online bookstore is a revolt in book industry. The old-style bookstores operative time, addresses and places are so much restricted, so the types of novels and books to be find found a degree of constraint. But the online bookstore ruined the management mode of outdated bookstore, as long as you have a computer, you can buy the book from anywhere, saving time and efforts, shortening the time of book selection link efficiently. The online bookstore system based on the standard of provides suitability and facility to people out there.
Push Technology: Impact and Issues

Internet Explorer 4.0 is one of the most advanced, modern browsers that can fully support the active desktop, push technology, multimedia, and much more. Using push technology, an electronic publisher with content aggregated from multiple sources applies the subscriber's interest profile to select information to deliver to the subscriber on an automatic basis. However, push technology provides the means to predeliver much larger packages of content. The market leader in push technology is currently PointCast. Push technology provides benefits such as reducing and managing the information overload and dealing with communication bandwidth bottlenecks. Using the Internet today, without the aid of a push application, can be tedious, time consuming, and less than dependable. The volume and dynamic nature of content on the Internet is an impediment to users and has become an ease-of-use issue.
LibGuides: Reading Library Material on Your Desktop: Home

This guide will show you, step-by-step, how to find electronic books, technical reports and articles from your library
Resource Scheduling Algorithm Based on Evolutionary Computation in Dynamic Cloud Environment

The growing types of resources and changing user requirements in the cloud environment bring great challenges to the resource scheduling problem. In order to solve the problem of resource scheduling in dynamic cloud environment, this paper constructs a virtual dynamic cloud environment resource scheduling model, which realizes resource scheduling by means of virtual machine migration. In this model, the energy consumption of the cloud environment and the quality of service of the cloud environment after virtual machine migration are taken as two optimization objectives. At the same time, we propose a new dynamic multi-objective optimization algorithm (called DCRS-EA) to solve the resource scheduling problem in dynamic cloud environment. DCRS-EA not only detects whether the environment changes, but also estimates the types of changes, in which different types of change are solved by different response strategies. Finally, the experiments show the superior performance of DCRS-EA when comparing to other dynamic strategies on the built optimization model.
Challenging the Stereotypes about Samyangdong Prehistoric Museum: A Critical Reading from a Gender Perspective

이 연구의 목적은초등학교 현장체험학습의 장소인 선사유적 박물관을 ‘젠더 관점에서의 비판적 읽기’(이후 젠더 읽기로 표기)를 통해 선사시대를 바라보는 정형화된 전시의 문제점을 밝히는 데 있다. 잘 알다시피 우리가 알고 있는 선사시대는 실제가 아니라 해석의 결과물이다. 따라서 선사시대를 바라보는 관점이 반영될 수밖에 없다 그렇다면 어떤 관점에서 과거를 재현하고 있을까? 이를 위해 하나의 사례로서 ‘삼양동 선사유적 전시관’에 주목하면서 우리나라 선사유적 박물관들이 ‘남성이 된다는 것’과 ‘여성이 된다는 것’라는 젠더 차별화가 관행으로 뿌리내리고 있음을 확인하고, 이를 통해 젠더 중립적 관점에서의 새로운 선사유적 박물관의 젠더 중립적 전시와 초등학교 현장체험 학습의 올바른 방향을 탐색한다.This article has aimed to challenge the stereotypes on prehistoric museum according to a critical reading from a gender perspective. Attention was given to the information provided by the museum that is preferred as a place for field experience learning. As a case study, how does the Samyangdong Prehistoric Museum constitute ‘female becoming’ and ‘male becoming’? In particular how does it invests in current or recent gender differentiation with roots, and thus legitimacy, by presenting them as permanent and essential ? Through this study, it was discovered that acceptance of the time depth covered makes it the educators responsibility to engage with the questions of where and how gender enters society as a distinct practice. This study proposes a new gender-neutral point of view to modify the exhibition direction of the Prehistoric Museum.
Penggunaan model cooperative script untuk meningkatkan keterampilan membaca pemahaman pada siswa kelas V di sekolah dasar

This research servers as an effort to improve student’s reading comprehension skills through the application of the Cooperative Script model for student 5 th grade of elementary school student at Surakarta on 2019/2020 school year. The subject of this study were 19 students from 5 th grade of elementary school and class teacher. This research is a classroom action implementation, observation, and reflection. Data collection methods used are observation, test, interview, and document analysist. This study uses descriptive data analysist with a qualitative approach that describe data obtained by researchers from the result of the implementation of the action. This study found success in increasing the average value from cycle I to cycle II, the average value of cycle I was 71,73 with classical completeness 36,84%, increasing in cycle II that was 85,18 with classical completeness 89,47%. The output of this study indicated that by applying the Cooperative Script learning model can improve student’ reading comprehension skill, student activity, and teacher performance
Grouping and Recurrent Feature Encoding Based Multi-task Learning for Pedestrian Attribute Recognition

Pedestrian attribute recognition (PAR) in surveillance is to predict pedestrian visual features (somatotype, wearing style, etc.). Existing methods usually elaborately design complex multi-label deep neural networks to solve it, which is hard to take advantage of attribute correlations and prone to suffering from the negative transfer problem. In this paper, we proposed a grouping and recurrent feature encoding based multi-task learning method to solve these problems. We group attributes adaptively based on attribute learning state and use Bi-direction recurrent neural network (Bi-RNN) to acquire the encodings of different groups to build a auxiliary learning task. We optimize group learning and feature encoding simultaneously in an end-to-end multi-task learning (MTL) manner. Furthermore, we establish dynamic loss module to enable the model learn the weight automatically for different tasks in a closed-loop way. Finally, after finishing training, the proposed method allow us to remove auxiliary module and merge all group into one to get a concise yet effective model without weakening the performance. Extensive experimental results in two public datasets, PA-100K and RAP has demonstrated the performance superiority of our method.
Introducing Machine Learning with Apache Mahout

This chapter covers Apache Mahout and the synergy between Apache Mahout and Lucene.
Hello World: The Lucene Way

This chapter covers indexing data with Lucene, specifically how Lucene stores and represents data, Lucene query nuances, and how Lucene facilitates multiparameter search.
Machine Learning Security Assessment Method Based on Adversary and Attack Methods

Analytical methods for assessing the security of Machine Learning Systems (MLS) that have been proposed in other researches do not provide compatibility with each other and their taxonomies have become incomplete due to the introduction of new properties of adversarial machine learning. In this sense, we have identified carefully relevant concepts of most prevalent researches about the security assessment of MLS. We propose a novel security assessment method based on the modeling of the adversary and the selection of adversarial attack methods for the generation of adversarial examples related to the also proposed taxonomy. This method provides compatibility with other proposed methods as well as practical guidelines and tools for evaluating machine learning systems. We also introduce the concern for efficient metrics capable of measuring the robustness of MLS to adversarial examples. This research is focused on the empirical evaluation of the security of machine learning systems, rather than on classical performance evaluation.
A Literature Review on Sentiment Analysis

This paper is an intend to consolidate the review and perform the literature survey on the sentiment analysis and on opinion mining. In this paper we try to analyze people sentiments, opinions, and emotions from their text language by which we can try to understand in what mood or emotion was the person while writing the text message. There are many types of sentimental moods according to which person writes the text it can be classified like happy, sad, neutral, angry. Also there are times when the user can be sad and angry at the same time which is needed to be identified by the analysis.
Implementasi Data Mining Untuk Market Basket Analysis Menggunakan Asosiation Rules Pada Minimarket 212 Mart Batam

Data mining is a method of searching for previously unknown information from a large database. The important information found to be valuable and beneficial for the making of a decision. The information gained should be precise and accurate because it was highly influential in decision making as well as the outcome of the decision, as was the information required by the Minimarket 212 Mart Taman Carina Batam. The minimarket is located close to the residents' housing and the school. Minimarket 212 Mart requires an analysis to find out consumer purchasing habits that would later be useful for organizing store layouts, make inventory of product efisien in order for sales transactions to run smoothly also increase sales results in minimarkets. Market basket  analys methods can be used to analyze the interrelationship of product that consumers buy at the same time to find out the consumer's purchasing habits. The study successfully found the combination of interrelated products that had the highest support value and confidence value on the combination of Snack, Baverage, Breakfast Food which were to have a 26,7% support value and 100% confidence
The atmosphere in the school class in the perception of primary school students

The article describes the research results regarding the atmosphere in the school class. The research used the diagnostic survey method and the survey technique. The author's survey questionnaire was used in the research, which included open and closed questions. The research shows that the majority of four-graders perceive the atmosphere in their school classes positively. The respondents like their classmates and feel safe in the classroom. Teachers influence the atmosphere of the classroom through their friendly attitude towards students as well as through conversations with students, help and support.
LibGuides: Remote Library Services for Online Learning: Interlibrary Loan

This guide offers links and answers questions for the online learning shift taking place in response to the COVID-19 outbreak.
A Survey on Contrastive Self-supervised Learning

Self-supervised learning has gained popularity because of its ability to avoid the cost of annotating large-scale datasets. It is capable of adopting self-defined pseudo labels as supervision and use the learned representations for several downstream tasks. Specifically, contrastive learning has recently become a dominant component in self-supervised learning methods for computer vision, natural language processing (NLP), and other domains. It aims at embedding augmented versions of the same sample close to each other while trying to push away embeddings from different samples. This paper provides an extensive review of self-supervised methods that follow the contrastive approach. The work explains commonly used pretext tasks in a contrastive learning setup, followed by different architectures that have been proposed so far. Next, we have a performance comparison of different methods for multiple downstream tasks such as image classification, object detection, and action recognition. Finally, we conclude with the limitations of the current methods and the need for further techniques and future directions to make substantial progress.
Research on Trusted Computing Scheme Based on Block Chain and Internet of Things

Abstract The popularity of blockchain, Bitcoin and Ethereum in 2017 can be described as an empty alley. However, the reason why such a popular technology has strong vitality must be to find the most suitable application. In view of the security and privacy, lack of resources, network transmission delay and other issues in the current Internet of Things system, analyze the advantages brought by the introduction of blockchain technology, and compare the architecture of the blockchain Internet of Things with the traditional Internet of Things system. Aiming at the problems existing in the application of blockchain IoT, a blockchain IoT architecture based on edge computing is proposed. In this architecture, the data collected by the edge device is filtered and transmitted to the fog node of the fog layer through the multi-interface base station, and the fog node reports the data processing result to the distributed cloud layer based on the blockchain. The fog layer provides positioning, and the cloud layer provides wide-area monitoring. It provides large-scale event detection, behavior analysis and long-term pattern recognition through distributed computing and storage, and combines blockchain technology to provide scalable, reliable and highly available Internet of Things services. Therefore, the proposed architecture has important reference significance for subsequent computer technology application research based on blockchain IoT technology.
Project-based Teaching Model of Physical Education Based on OBE

The promulgation of National Medium-and Long-Term Education Reform and Development Plan (2010-2020) marks the cultivation of high-quality applied talents from the supply side is an important task for talents training in colleges and universities. Based on the literature and fieldwork, this paper aims at the current situation of the cultivation of physical education professionals in China. Based on the OBE education concept, this paper proposes the application of physical education professionals who take students as the main body and knowledge and ability as the main line. Under the guidance of talent training, we will build a multi-level project-based teaching model combining professional main course learning, professional core competence training and comprehensive ability training. Through the completion of the project to realize the organic combination of knowledge learning and ability training, train students to solve physical education. Teaching practical problems, innovative practices and the ability to learn for life.