Reviewerly/exHarmony huggingface dataset:
Genetic Environments of the Eunjeok Au–Ag Deposit in the Yeongam District: Implications for Cretaceous Epithermal Au–Ag Mineralization in South Korea

Eunjeok Au–Ag deposits are situated in the Yeongam district, Cheollanamdo-province, South Korea. They are genetically related to the Bulgugsa magmatic event (ca. 110–60 Ma), caused by the transition in the subduction direction and style of the Izanagi Plate. Three gold- and silver-bearing hydrothermal veins filled the fractures of the Cretaceous rhyolitic tuff. The major ore minerals were arsenopyrite (31.47–32.20 at.% As), pyrite, chalcopyrite, sphalerite (8.58–10.71 FeS mole%) and galena with minor amounts of electrum (62.77–78.15 at.% Au), native silver, and argentite. Sericitization was dominant in the alteration zone. The various textures of quartz veins (i.e., breccia, crustiform, comb, and vuggy) may indicate the formation of an epithermal environment. The auriferous fluids with the H2O–NaCl system have homogenization temperatures and salinities of 204 °C to 314 °C, less than 10 wt.% equiv. NaCl, and experienced mixing (dilution and cooling) events during mineralization. Considering the characteristics of the geologic setting, major fault system, and host rock, the Eunjeok Au–Ag deposit within the Yeongam district tends to share the general geologic characteristics of Haenam–Jindo epithermal mineralization episodes. However, the age of gold–silver mineralization (86.0 Ma) is older than that of Haenam–Jindo epithermal mineralization episodes (&lt;70.3 Ma), implying some differences exist in the genetic sequence of extensional characteristics caused by transcurrent Gwangju–Yeongdong faults.
Practical Relative Order Attack in Deep Ranking

Recent studies unveil the vulnerabilities of deep ranking models, where an imperceptible perturbation can trigger dramatic changes in the ranking result. While previous attempts focus on manipulating absolute ranks of certain candidates, the possibility of adjusting their relative order remains under-explored. In this paper, we formulate a new adversarial attack against deep ranking systems, i.e., the Order Attack, which covertly alters the relative order among a selected set of candidates according to an attacker-specified permutation, with limited interference to other unrelated candidates. Specifically, it is formulated as a triplet-style loss imposing an inequality chain reflecting the specified permutation. However, direct optimization of such white-box objective is infeasible in a real-world attack scenario due to various black-box limitations. To cope with them, we propose a Short-range Ranking Correlation metric as a surrogate objective for black-box Order Attack to approximate the white-box method. The Order Attack is evaluated on the Fashion-MNIST and Stanford-Online-Products datasets under both white-box and black-box threat models. The black-box attack is also successfully implemented on a major e-commerce platform. Comprehensive experimental evaluations demonstrate the effectiveness of the proposed methods, revealing a new type of ranking model vulnerability.
Research on Improvement of N-grams Based Text Classification by Applying Pointwise Mutual Information Measures

In the present paper, the text classification is examined, which is applied after extracting N-grams of words to obtain characteristics describing the text documents in the collection.The selection of the most important features in regard to the pre-defined categories is made.The built vector space model for representation of text documents is modified by pointwise mutual information (PMI) measures.The conducted experiments include computation of the accuracy and F-measure of text classification with different methods for feature selection, different number of selected attributes (N-grams of words) for different classifiers and different datasets.The results obtained show an improvement in the performance of the classification of short texts with unbalanced categories.
Do cryptocurrencies really have (no) intrinsic value

Depending on the chosen perspective, cryptocurrencies either constitute a unique opportunity to end national patronizing built on debt-based fiat money (currency) or a menace to a well-established financial order that ensures economic stability. A central issue in the heated debate surrounding cryptocurrencies is whether they have any intrinsic value at all. In this conceptual position paper, we briefly summarize existing standpoints and suggest three alternative propositions: (1) to avoid using the term “intrinsic value” for the valuation of cryptocurrencies, (2) to refer to the sum total of all properties that could potentially qualify them as money, and (3) to consider the amount of capital and energy that is needed to create them. These suggestions bear substantial implications for the economic classification of cryptocurrencies.
A Study on the Effect of Government Regulations and Regulatory Improvement Policies on the Innovation Efficiency of Logistics Companies

The government has been promoting various policies supporting innovation in the logistics industry in response to the 4th industrial revolution. However, in the domestic logistics industry, the innovation and introduction of new logistics technologies has been delayed, and launching innovative new businesses are discouraged due to an inadequate legal system and rigid regulations.<BR> In that sense, this study measures the innovation performance of domestic logistics companies and impacts of various government regulations and regulatory improvement policies on innovation performance. As a result, regulations such as ‘Financial Market Regulation,’ ‘Separation of Banking and Commerce,’ and ‘Protection of Intellectual Property(IP) Rights’ and one regulatory improvement policy, ‘Relaxation of Anti-Competitive Regulations,’ positively impacted innovation efficiency. Accordingly, this study provides practical implications for managers as well as policy makers as to which regulations and regulatory improvement policies lead to higher innovation performance in the logistics industry. The implications of this study help managers gain deep insights to achieve innovation performance and help policy makers establish innovation supportive regulations and policies in the future.
Self-Designed Learning in Nooks: Exploring alternatives to mainstream education

During the COVID-19 pandemic, children and youth paid a heavy price as schools and colleges closed, social gatherings and sports activities were prohibited, and young people’s once bright, promisin...
Time Delayed Effect Can Bring Novel Hierarchical Complex Dynamics to Neural Network?

A recurrent neural network model with including time delayed effect is investigated by means of theoretical consideration and computer experiments as well. The detailed contents were already published in Neural Computing and Applications, 11 (3 and 4), pp. 137–143 (2003) by Suemitsu, Y., & Nara, S., and this report was written only for an oral presentation of this work in ICCN2019.
Health Auditing and Administration Using IoT with the Help of Cloud

One of the biggest applications created with the Internet of Things (IoT) is advanced online health administration system. Using sensors which are worn or are either present in networks gives huge amount of data which are related to the physiological health of consumers. By collecting and analysing this information, one can meet big challenges in the domain of health care system. With the help of this amount of information and processing techniques, we can bring some of the biggest changes in the domain of health administration system such as (a) With these techniques and information we can replace the post disease treatment with pre-disease treatment (b) It can also help in making personal profile of patients and so, profile treatment which is required by patients can be done. (c) It also helps in minimizing the operating cost while maximizing the output of the health administration system. This paper shows the convenience and risks associated with the use of IoT for achieving the dream of the advanced health administration system.
Collaborating in The Midst of the Pandemic: Chilean and Filipino Elementary Teachers Exchanging Online Pedagogical Initiatives

COVID-19 poses a global challenge on class delivery among teachers who, in general, have not been directly trained to work under such modality.In both Chile and the Philippines, governments have mandated no face-to-face learning until a vaccine is produced or the current situation improves.These particular issues have increased anxiety and uncertainty in educators and students in both countries.This ongoing research is a collaborative project between elementary teachers in Chile and The Philippines exchanging experiences about their online teaching practices.Five language and mathematics teachers, in each country, will perform mutual online class observations and also engage in collaborative reflections over a period of two months.The objective is to examine the technical, pedagogical, and human aspects of virtual teaching and learning under these challenging circumstances.A qualitative analysis of the observation notes, the transcription of teachers' post-lesson reflections, the surveys to teachers, students, principals, and parents will be performed using ATLAS.ti.Moreover, the researchers will utilize Borich's Eight Lenses for Classroom Observation (2014) to analyze teachers' lessons during their observation.The researchers hypothesize that similar issues and online practices will emerge in the discussions.Furthermore, it is also believed that the feedback from principals, students, and parents may influence teachers' preparation as well as their reflections of online classes.This study, therefore, aspires to provide a model on how teachers across borders can collaboratively learn and reflect.It also aims to shed light on the current perspectives that teachers, students, principals, and parents have towards online education.
Terraform Best Practices

Finally, we are at the last chapter of this book. Terraform offers multiple ways to implement configurations. Technically, they are all valid solutions, and Terraform will not complain about which one you use. However, it is important to evaluate whether the chosen technique for configuration implementation is generic, promotes reusability, is extensible, is secure, and promotes collaboration. This chapter is about implementing Terraform configurations using best practices. This chapter will cover the practices to employ when using various features of Terraform. It will provide best practices related to providers, versioning, variables, outputs, authentication, and many other aspects.
Gesture Recognition Analysis Based On Monocular Vision Relying On Human-Computer Interaction Filtering Algorithm

The progress of vision-based gesture recognition technology has introduced a brand new way of human-computer interaction (HCI). However, due to the complexity of feature extraction, gesture recognition based on monocular vision has become a research hotspot and bottleneck. In this paper, static gestures are combined with the CSS feature description to extract the skin-color model based on the HCI filtering algorithm first. Subsequently, the fusion feature is established. Finally, feature recognition is performed based on the HCI filtering algorithm to implement gesture recognition analysis based on monocular vision. The practice has demonstrated that the proposed algorithm has a relatively high recognition rate for complex gestures with the sign language of high local similarity.
Listening Comprehension Problems at The Fourth Semester Students of English Education Department at Sultan Ageng Tirtayasa University

This research was aimed to find out the problems and the causes of problems faced by fourth semester students in listening comprehension at English Education Department University of Sultan Ageng Tirtayasa. The qualitative descriptive design was applied in this study. The data were collected from questionnaire and interview. This study used data reduction, data display and conclusion drawing in analyzing data. This study used methodological triangulation to gain the credibility of the study. The result from the students’ problems in listening comprehension was divided into three categories. First, listening comprehension problems related to listening material such as unfamiliar words, poor grammar, understand every single word, length of the text, interpreting meaning, fatigue, unfamiliar topic, reduced form and background knowledge. Second, listening comprehension problems related to listener such as understanding listening, anxiety, unclear pronunciation, intonation of speaker, recognize signal, lose focus, unknown word, infer meaning, predict next discussion, memory and misinterpretation task. Last, listening comprehension problems related to physical setting such as bad quality of recording, hesitation & pause, lack of visual support, variety accents, speed of delivery, inability get repeated, and noises. Besides, the causes of problems in listening comprehension such as listening has a complex process, limited time, unclear pronunciation, length of the text, poor of recording, sleepy, noisy, lack of practice and lack of background knowledge. So the researcher hopes the next researcher will perform a better comprehension such as discusses further about the causes of the problems and promoting techniques to solve the listening problems.
IP protection for computer programs

Chapter five discusses the legal developments in computer program protection. I explain how and when legal protection for computer programs evolved and outline the IP protection legal mechanism awarded to programs. I also present the more current legal challenges and provide further insight toward the expected changes.
Power-weighted kNN Classification for Handling Class Imbalanced Problem

The class imbalanced problem is one of the significant classification issues, which has gained attention in several years. Modifying the classification model to effectively work with the imbalanced datasets is an interesting alternative method in addition to directly adjusting the datasets. Due to the excessive presence of majority class neighbors, the k-nearest neighbors (kNN) classifier is one of the models that difficultly classifies the imbalanced datasets. Accordingly, a novel weighted kNN model is introduced in this paper to handle such a problem, called power-weighted kNN classifier. The proposed power-weight assignment, which is in the form of a power function, is applied to determine the weighted values for each instance. It depends on three factors that are (1) the class of considered instances, (2) the proportion of classes of their nearest neighbors, and (3) the imbalanced ratio of the dataset. The experimental results show that the power-weighted kNN classifier significantly outperforms other kNN models in terms of recall. It also shows greatly improved precision compared with the methods applying the oversampling technique. Moreover, the power-weighted kNN classifier yields the best results over all other models when measuring by the area under the ROC curve.
Cyberstalking: reflection in national legislation

The article is devoted to cyberstalking – a type of specific cybercrime in which psychological pressure on the victim occurs with the help of IT-technologies, and its reflection in national legislation.
The Use of Hello English Application to Improve Students’ Vocabulary of Junior High School

This study aimed to improve the students’ vocabulary using English Hello Application. This design were classroom action research with four stages of two cycles. The subjects were 22 students from seventh grade students in a junior high school Sukoharjo. The researchers used three instruments to collect the data which were test, observation sheet, and questionnaire. The result showed that the students’ vocabulary could improve by using English Hello application from cycle I by 51.81 for the mean of pre-test result and 69.54 for the mean of post-test result. Cycle II was 78.63 for the mean of pre-test and 91.81 for the mean of post-test. The result of t-test in cycle I and cycle II were significant. In addition, the minimum completeness score of pre-cycle, cycle I, and cycle II increased significantly. There was a positive response of using English Hello application by most of students chose strongly agree with 8 students in cycle I. It increased in cycle II by most of them who chose strongly agree with 11 students in learning vocabulary using English Hello application.
Cloud Native Trends

I hope by now everyone has a clear view of the end-to-end lifecycle of cloud-native systems from architecture to design to development to operations.
KEFEKTIFITASAN MODEL PEMBELAJARAN TWO STAY TWO STRAY TERHADAP KEMAMPUAN BERBICARA SISWA KELAS IV SD NEGERI MANGUNHARJO SEMARANG

The background of this research is the still centered learning of the teacher and the lack of courage of students to express an opinion, this is also supported by the incompleteness of Indonesian language learning, precisely in the speaking ability of fourth grade students of SD Negeri Mangunharjo Semarang. This study aims to determine whether the two stay two stray learning model is effective on the speaking ability of fourth grade students of SD Negeri Mangunharjo Semarang. This type of research is quantitative research using Pretest-Posttest one-Group Design. After taking the data, then analyzing the data of the pretest and posttest learning outcomes with the t-test that was obtained with an average pretest value of 57.12 and an average posttest value of 80.19. With N = 26, obtained tcount = 17.29282 with a 5% significance level of 2.055529. Because tcount = 17.29282&gt; table = 2.055529. Then this shows that the t test has a significant effect. This shows that there is an effect of learning the Two Stay Two Stray (TSTS) model. Suggestions that can be delivered by researchers to teachers is that learning is not only centered on the teacher, but also involves the activeness of students in order to achieve enjoyable learning and students have an interest in learning.
Integrating Earth Science GNSS &amp; Satellite Thematic Service Preliminary Data and Products Results on SETTING Platform

Summary The latest years reveal to us the necessity and the interest to develop an integrated research platform to improve skills in answering fundamental scientific questions in the field of Earth sciences and questions in the socioeconomic field related to geo-hazards and geo-resources at the European level, a platform known by EPOS - European Plate Observing System. Main objectives such as the implementation of thematic services (TCS) for different communities in EPOS, the development of integrated services (ICS) for interoperability, data management and access to services, ensuring the long-term financial and legal sustainability of EPOS - ERIC and implementing services lead to the harmonization of EPOS implementations with the national strategy. As a result, many European states mirror the EPOS platform at the national level and Romania is one of them (Integrated thematic services in the field Earth Observation - A national platform for innovation – SETTING). An electronic research infrastructure was developed for data integration of products and services and offered to users. This contributed to building a community for Earth Sciences by promoting cooperation with complementary projects in geosciences (Geo, ICT, and environmental sciences) and offering services to different users and authorities.
Yahoo data breach settlement: How to claim the cash

The billions of people who had their sensitive information snatched from their Yahoo accounts between 2013 and 2016 are now eligible for two years of free credit-monitoring services and other potential restitution in a legal settlement valued at $117.5 million for repeated data breaches.
INTERNET OF THINGS UNTUK MONITORING GEJALA KECEMASAN PADA PASIEN MENGGUNAKAN LOGIKA FUZZY

A patient should not be in a psychologically worrisome condition for fear of lowering the temperature causing slow healing to last a long time. Prolonged anxiety will develop into stress, so it is very necessary to detect anxiety early before anxiety persists and results in stress. However, these anxiety symptoms are related to the same psychological factors and contain uncertainties that cannot always be controlled and monitored by doctors. The purpose of this research is to create a system that can monitor the patient's anxiety symptoms in real-time based on the Internet of Things (IoT) so that doctors can determine the right treatment to maintain the patient's psychological condition. The system detects responses in humans when someone feels anxious, namely heart rate, body temperature, and sweat intensity which are detected using sensors. The information obtained from the sensor becomes input parameters which are then processed using fuzzy logic to detect early symptoms. Fuzzy logic was chosen because it is a method for solving fuzzy problems with the uncertainty of the threshold value of symptom change. The output is in the form of anxiety symptoms which are divided into 3 (three) symptoms, namely normal, mild, and severe. The research method used is the SDLC (System Development Life-Cycle) method. the results based on the black box test state that the entire functional system works according to its function, the white box test results state that all logic is correct and appropriate. The results showed that the system that had been built succeeded in monitoring anxiety in patients with a system accuracy of 98%.
METHODICAL BASES OF FORMING TEENAGERS’ SOCIAL EXPERIENCE UNDER THE CONDITIONS OF EXTRACURRICULAR EDUCATIONAL WORK

The article reveals the problem of scientific and methodical support of the process of forming social experience of pupils in secondary school. Experience is seen as a mechanism of historical, cultural and social inheritance, and social experience - as a source of regulation of public life, the establishment of qualitatively new relationships between people and groups. The characteristics of concepts «social experience of teenagers» and «forming of teenagers’ social experience» are given. The functions of social experience (cognitiveinformational, communicative, evaluative-representational, activitypractical, and creative) are singled out. Interaction is defined as the main determining factor of gaining social experience, because the participation in it determines the means of activity used by a person, personal reactions, symbolic meanings, etc. The most expedient for formation of teenagers’ social experience forms of organization of extracurricular educational work (collective, group and individual) and its types are identified and characterized. The main methods of extracurricular educational work on the formation of teenagers’ social experience (discussion, training, group problem solving, individual research tasks, training, assignment, ethical conversation, method of reflection) are revealed. The means of forming social experience of pupils are determined.&nbsp