Reviewerly/exHarmony huggingface dataset:
Estimating Certain Integral Probability Metrics (IPMs) Is as Hard as Estimating under the IPMs

We study the minimax optimal rates for estimating a range of Integral Probability Metrics (IPMs) between two unknown probability measures, based on n independent samples from them. Curiously, we show that estimating the IPM itself between probability measures is not significantly easier than estimating the probability measures under the IPM. We prove that the minimax optimal rates for these two problems are multiplicatively equivalent, up to a log log(n)/ log(n) factor.
Communicators in e-learning – recommendations for teaching practice at the times of coronavirus COVID-19 – report from pilot research

The text presents an excerpt from qualitative research conducted in the situation of coronavirus COVID-19 at Nicolaus Copernicus University in Torun. 50 students took part in the qualitative research. The aim of the aforesaid research was to determine the ways in which students use Internet tools for educational purposes at the time of the pandemics and what are their expectations concerning the educational use of Internet communicators by their lecturers. The research was to diagnose the state of e-learning (with respect to the group of NCU students) and, after data analysis, to make recommendations for educational practice. The results obtained show that the majority of students use communicators for educational purposes, especially to work on projects with their colleagues. They also seek help in a group of their friends, whereas lecturers rarely appreciate possibilities of using communicators in education.
Application of Edge Computing and SCADA System in Second Class Substation

This article adopts the way of progressive transformation of edge calculation and the combination of the substation, this paper makes a brief introduction to the calculation of edge, and describes its development situation at home and abroad, and then stand for intelligent SCADA system on 750 kV substation briefly, the architecture will eventually margin calculation and combination of SCADA system, discuss the practicability of EC SCADA system.
DEVELOPING THE STUDENTS’ ABILITY IN SPEAKING THROUGH IDEAS FUNNEL STRATEGY IN CLASS X TKJ AT SMK NEGERI 1 GUNUNGSITOLI BARAT IN 2020/2021

As the students of class X TKJ at SMK Negeri 1 Gunungsitoli Barat in 2020/2021 mostly failed in the middle semester test of English subject, the researcher notified problems such: a) The students were unable to express ideas through speaking; b) The students lack of vocabulary. Thus, CAR (single cycle with four meetings) was carried out to develop the students’ ability in achieving better final result. It is concluded that Ideas Funnel strategy developed the speaking ability of the students. Finally, the researcher writes some suggestion, namely: 1) Fellow English teachers at SMK Negeri 1 Gunungsitoli Barat is suggested to use Ideas Funnel Strategy to develop the students’ ability in speaking skill, and 2) The future researchers need to conduct the relevant research by using Ideas Funnel Strategy in English speaking competence.
An Intuitive Extensible Framework for Implementing Cloud Broker Architectures

Cloud computing is broadly received gratitude to the high business spryness; it assurances to its shoppers. Cloud administrations arrangement in the commercial center is an essential undertaking for both cloud customer and cloud supplier principally if the cloud buyer asks explicit properties for its applications. In this manner, this undertaking is designated to a third part which is the cloud intermediary. The proposed framework a cloud asset dealer is suggested that will administer the task of suppliers’ assets to purchaser progressively. The proposed representative uses different prerequisites and imperatives determined by the shopper in the necessity depiction format as contribution, to figure amassed necessities, utilizing an accumulation calculation. Further, the administration planning calculation is characterized to discover a streamlined match between the accumulated necessities with the suppliers contributions. From that point, this calculation is executed regularly, in view of a procedure for dynamic planning to profit customers by virtue of presentation of new supplier or some great contributions. Results demonstrate that the arrangement gave by agent ends up being a success win circumstance for the customer concerning cost just as execution. We propose a monetarily roused pay way to deal with increment the granularity and utility of saved calculation and capacity administrations. The result is a profoundly virtualization of cloud asset intermediary. It comprises of a guardian asset administration commercial center and a shopper configurable virtual machine for asset sharing. The framework bolsters progressively settled virtualization with powerfully customizable asset limits for fine-grained auxiliary, worldly, and vertical–spatial versatility.
A Framework for Dry Waste Detection Based on a Deep Convolutional Neural Network

Due to lack of proper regulations in many areas of the world, consumers are not mandated to waste sorting at the origin of the source. Moreover, human sorting often suffers from human errors and low accuracy. In the intelligent detection system, it is attempted to break down a variety of household wastes including plastic bottles, glass, metals, paper bags, compact plastics, paper and disposable containers. In this paper, a real waste image system is investigated using the deep convolutional neural network and a remarkable accuracy of 92.76% was achieved.
ASSESSING THE SIXTH SEMESTER STUDENTS’ TRANSLATION QUALITY OF SHORT STORY “RUANG ISOLASI UNTUK SI GILA”

Concerning to the accuracy and clarity of translation equivalence in Indonesia-English and vise versa, the translation quality of English Education students' at the IKIP Gunungsitoli was undetermined; some problems such as mistranslation and untranslated words were found in the students’ translation. Through a descriptive qualitative study, the translation quality of Sixth Semester (6th) English Education Study Program considering the three aspects: accuracy, readability and acceptability of short story text by title “Ruang Isolasi Untuk Si Gila”. The research used applied electronic dictionary( on/off line) and google translate to translate, moreover the researcher separate the short story text into sentence form. The data were analyzed using Nababan’s scale based on Shuttleworth and Cowie’s theory of translation quality in considering the three aspects: accuracy, readability and acceptability. The results showed that percentages of Accuracy: 52% accurate, 42% less accurate and 6% inaccurate for students translation, while accuracy: 69% accurate, 30% less accurate and 1% inaccurate for native revision. Readability: 97% readable, 3% less readable and unreadable not founded for students translation, for native’s speaker shows that the data readability: 97% readable, 3% less readable and not readable not founded for native revision. Acceptability: 100% acceptable, less acceptable not founded and not acceptable not founded for students translation, while acceptability: 99% acceptable, 1% less acceptable and not acceptable not founded for native revision. The conclusion was translation quality that was done by sixth semester students of English Education Study Program is relatively show the meaning of source text (ST) meet expectation for the reader eventhough there are mistakes that fifth semester student did when translating the text.
Special Issue on The Workshop on MAthematical performance Modeling and Analysis (MAMA 2019)

The complexity of computer systems, networks and applications, as well as the advancements in computer technology, continue to grow at a rapid pace. Mathematical analysis, modeling and optimization have been playing, and continue to play, an important role in research studies to investigate fundamental issues and tradeoffs at the core of performance problems in the design and implementation of complex computer systems, networks and applications.
Service Innovation of University Library in the Big Data Era

In the era of big data, the extensive application of data resources provides strong support for the reform and innovation of university library reader services, and provides new development ideas for the innovative development of reader services.This paper studies the challenges faced by the reader service of university libraries in the era of big data, and puts forward suggestions to improve the reader service level of university libraries.However, how to find effective information in complex information requires not only the uniqueness of university library services on the basis of maintaining common services, but also the need to strengthen the research on improving library service innovation models and methods.The university library in the big data environment, through the construction of a library service sharing platform and a cloud service model, proposes a library service innovation strategy in the big data era, improves the efficiency of the integration of book resources in the form of a regional alliance, and realizes the library Large-scale management and reservation of resources to realize the innovation of service content.Based on the service practice of university libraries, this paper analyzes the common problems in service innovation of university libraries, and proposes big data under the strategic background of optimizing service innovation of university libraries, and provides references for service innovation of university libraries.Practical results show that the innovative services of libraries need to use scientific methods and attitudes, treat big data and innovative services of university libraries from a development perspective, and be good at using big data for innovative services of university libraries.
Digital Lean Operations: Smart Automation and Artificial Intelligence in Financial Services

The financial services industry covers banks, insurance companies and investment managers, as well as transaction or message processing companies. To streamline billions of daily transactions, lean principles and operational excellence programs have found theirway to financial service firms. Today, the resulting cost and risk reductions are further enhanced by embracing newdigital technologies—such as those falling under the umbrella of Industry 4.0. These digital technologies stimulate a new wave of operational efficiency improvements by making processes more automated, autonomous, and smart. Inspired by Boute and Van Mieghem (2021), we provide a framework to evaluate the transition towards digital, autonomous and smart operations in financial services. We report our findings from the digital operations journey of Euroclear, a service provider of settlements for securities transactions, on their quest for increased automation and autonomy. We also shed light on the potential of artificial intelligence in financial services. Data-driven solutions may support financial service firms from purely descriptive models and methods with strong predictive power, towards prescriptive decision-making algorithms.
Aplikasi Sistem Pendukung Keputusan Dalam Menentukan Rekomendasi Sekolah Menengah Atas (SMA) Negeri Di Kota Madiun Dengan Metode Weighted Product

Application of Decision Support Systems in Determining Public High School (SMA) Recommendations in Madiun City with the Weighted Product Method is a system that provides information in the form of online school recommendations, thus helping prospective students to find out the school of their choice. The problem that exists today is the number of admissions paths for new students. Starting from the value report card path, achievement path, and zoning path. This encourages researchers to create an information system that can assist prospective students in determining the school of their choice. With a decision support system, prospective students can predict that they will be accepted at the school of their choice or in another school. The DSS method used in this study is the Weighted Product Method. While the software development method used is the waterfall method. Software development is done using PHP as a programming language, then MySql as the database server, and Code Igniter as the PHP framework. Testing on Decision Support System Applications in Determining Recommendations for Public Senior High Schools (SMA) in Madiun City with the Weighted Method was tested by questionnaire and black box testing. Questionnaire testing uses the System Usability Scale (SUS) to measure the system usability from the user's point of view in using the system. Black box testing is focused on the functional system so that the system runs properly.Keywords: School, SPK, Weighted Product.
KETERAMPILAN BERBICARA DALAM BAHASA LISAN BAGI MAHASISWA

Students who have good speaking skills, the conversation will be easier to understand by listeners. Speaking supports reading and writing skills. Writing and speaking have in common, namely as language production activities and convey information. The ability of students to speak will also be useful in listening and understanding reading activities. The conclusion that can be drawn is that Talking is a system of audible and visible signs that utilize a number of muscles of the human body for the purpose and purpose of combined ideas or ideas. Speaking is a form of human behavior that utilizes physical, psychological, neurological, semantic, and linguistic factors. Suggestion: with the importance of the speaking aspect of teaching Indonesian especially for elementary school students, educators must be able to provide motivation to develop speaking skills in students.
Kinship Verification Using Convolutional Neural Network

Kinship verification refers to finding a blood relationship between people. Facial images can be used to establish the relationship using feature extraction and matching. Kinship verification is an emerging topic for research in computer vision. The main task of kinship verification is to determine kin relation from a given pair of facial images. It is a binary classification problem that answers yes or no based upon whether the relationship exists or not for a given pair of images. The principle behind kinship verification is that every child inherits some of his parent's facial features. It has many real-world applications like finding missing children, image annotation, automatic photo management, and social media image tagging, etc. Convolutional neural networks have been used recently for classification problems in digital images. The major research contributions by CNN in solving kinship verification problems have been analyzed in this chapter.
Geochemical aspects of estuarine system in the cochin port trust Area: Appraisal of adsorption properties of PB(II), (CD II), ZN(IJ) AND CU(IJ) Onto the sediment-clay fraction

The aim of the present work is to explore the effective utilization of natural clay separated by Carver Process fi'om the sediments of Cochin Port Trust area, Kerala, India. Natural clay is found to be a good adsorbent in removing heavy metals such as Pb(ll), Cd(ll), Zn(ll) and Cu(ll) from an aqueous phase. Adsorption capacity of the adsorbent towards these four metal ions were determined by batch adsorption studies. The optimum pH obtained was 6.0 and the maximum adsorption capacity of Pb(ll), Cd(ll), Zn(ll) and CU(ll) was found to be 76.9, 78.5, 92.8 and 98.4% respectively. An optimum contact time of 120 min was observed for the uptake of heavy metal ions onto natural clay at 303 K. Also the kinetics of adsorption towards Pb(ll), Cd(ll), Zn(Il) and CU(II) were found to be of pseudo-second-order. The present study suggests that natural clay separated from the sediments of Cochin Estuary is highly efficient in removing the toxic heavy metal ions Pb(Il), Cd(ll), Zn(ll) and Cu(U) ii-OI11 aqueous solutions.
Анализ аспектов невербальной коммуникации между преподавателем и обучающимися в образовательном процессе

The article deals with various aspects of non-verbal communication between a teacher and students in a learning situation. In the introduction, the authors reveal the relevance of the topic, which is determined by the trends of transformation of modern education, one of which is a more intensive use of active teaching methods. However, the use of such methods is impossible without improving the quality of interaction between participants in the educational process. The novelty of the research lies in the analysis of the components of non-verbal communication, as well as in the analysis of the impact of non-verbal communication in General on the quality of teaching and interaction between teachers and students. The theoretical substantiation, the authors discuss the work of Russian and foreign authors in the following areas: the correlation of the verbal and nonverbal communication, types of nonverbal communication used in the learning process, analysis of the impact of nonverbal communication on the quality of teaching and interaction with students, the opinion of teachers about nonverbal communication in learning situations. In discussion of results, the authors summarize the main research topics: 1) substantiates the importance of combining the teacher skills verbal and non-verbal communication to ensure a holistic and integrated educational process; 2) the need to acquire tutor a wide range of nonverbal means for compliant and effective interaction with students; 3) due to the fact that the learning process is inseparable from the process of pedagogical communication, improving the quality of communication through the strengthening of the nonverbal side may lead to improving the quality of the training. In conclusion, the authors emphasize the importance of using non-verbal communication to create a motivating, comfortable environment for students.
Deep Q Learning from Dynamic Demonstration with Behavioral Cloning

Although Deep Reinforcement Learning (DRL) has proven its capability to learn optimal policies by directly interacting with simulation environments, how to combine DRL with supervised learning and leverage additional knowledge to assist the DRL agent effectively still remains difficult. This study proposes a novel approach integrating deep Q learning from dynamic demonstrations with a behavioral cloning model (DQfDD-BC), which includes a supervised learning technique of instructing a DRL model to enhance its performance. Specifically, the DQfDD-BC model leverages historical demonstrations to pre-train a supervised BC model and consistently update it by learning the dynamically updated demonstrations. Then the DQfDD-BC model manages the sample complexity by exploiting both the historical and generated demonstrations. An expert loss function is designed to compare actions generated by the DRL model with those obtained from the BC model to provide advantageous guidance for policy improvements. Experimental results in several OpenAI Gym environments show that the proposed approach adapts to different performance levels of demonstrations, and meanwhile, accelerates the learning processes. As illustrated in an ablation study, the dynamic demonstration and expert loss mechanisms with the utilization of a BC model contribute to improving the learning convergence performance compared with the origin DQfD model.
Limited Impact of Business Development Programs on Entrepreneurs' Profitability in the Presence of Ambiguity Aversion

This paper develops a theoretical framework to explain a limited effect of business development programs (BDPs) on entrepreneurs' profit. We argue BDPs limited effect is due to mismatch between a BDPs' narrow focus on business-promoting strategies and a wider context in which microentrepreneurs operate. Entrepreneurs are ambiguity-averse and have multiple sources of income, e.g. business and wage incomes, that are correlated with each other. We show that for a sufficiently ambiguity-averse entrepreneur with multiple income sources efficient training can result in profit decline. We, further, show that both the ambiguity aversion and the multiplicity of income sources are crucial for our results. Only when the wider context (multiple income sources, ambiguity-aversion) is considered, the business-training impact is limited and can result in post-training profit decline. The limited impact is caused by the diversifying role that the business income plays in households' finances.
Edge-Based Blockchain Design for IoT Security

This chapter gives an overall summary of how edge-based blockchain design can be implemented for IoT security. The proposed design addresses how the whole blockchain design can be made lightweight enough to execute at the network edge, such as on one or two Raspberry Pi 3 or 4 development boards. Issues such as the Proof of Work, consensus algorithm, and authentication type (public/private/hybrid) are addressed in this chapter. The proposed edge-based blockchain (eBC) is applied to protecting the integrity of data from smart meters. Both short-term and long-term anomalies in smart meter data are monitored by the proposed eBC system, through smart contracts. Further, IoT device virtualization is also achieved through Docker container implementation at the edge (in Raspberry Pi 3/4), along with Kubernetes orchestration. The eBC modules are thus deployable at run-time via the Kubernetes orchestration in Docker containers. Experiments show the robustness and efficiency of the proposed eBC modules.
Comparison of Spread Spectrum with Redundant Pattern Coding In Securing Text Messages Into Audio: Comparison of Spread Spectrum with Redundant Pattern Coding In Securing Text Messages Into Audio

The transmission of information from one place to another is mostly constrained by the security problems of the information itself. Moreover, this information is very confidential, so not just anyone can open it. One of the ways that can be done to hide confidential information is by using cryptographic techniques, namely by encoding the information using certain algorithms. The second way is to insert the information into certain media, such as digital images or audio, so that the information will be hidden and what will appear is the media only, while the information is disguised. In this study, the comparison of the Spread Spectrum steganography algorithm with the Redundant Pattern Coding algorithm to secure text messages in audio files. The data used are audio files with a size between 200 Kb to 265 Kb and text with a size of 50 bytes to 275 bytes. The experimental results obtained stego audio files from the insertion of the Spread Spectrum algorithm with an average PSNR value of 41,138 db and for the Redundant Pattern Coding algorithm the average PSNR value was 29,885 db.
METODE PEMBELAJARAN INQURY DALAM MENINGKATKAN KEMAMPUAN MENULIS TEKS PIDATO

The ability to write the speech text is one that must be mastered by the classical student in the field of reading, that is, by putting ideas and ideas into written form is not easy. After observations and interviews at the elementary school of the Komplek Ciampel, a number of writing problems have been identified with the factors involved in teachers, students, the media, and the learning models used in learning. The research aims to find out the difference in the ability to write down the text of students' speeches and to describe the inquiry's methods as more effective than the discovery learning model in developing the ability to write speeches on student VI elementary schools of Komplek Ciampel. This kind of research is the inquiry method in the posttest form. So selected the sample of the VIa class experiment group as an experiment class and the VIb class as a control class. The results of this study indicate a significant difference between the experimental class and the control class is seen in the higher average experimental class than the control class.