Reviewerly/exHarmony huggingface dataset:
Bitcoin Price and Miner Behavior an Application of ARDL Model

Bitcoin price volatility has always been a hot topic in the economic world as well as the academia, and many researchers have explored the price dynamic formation from different aspects. This study employs the AutoRegressive Distributed Lag (ARDL) Model to explain the bitcoin price formation from the perspective of miners hoarding behavior.
Pengaruh Pelatihan Penilaian Praktik Seni Budaya Berbasis Pergelaran bagi Guru Seni Budaya SMK di Salatiga

Art education is one of the major determinants in improving the skills of 21st century students. Various assessment in art education is held to create active and creative students, one of them is the performance-based arts and culture assessment. The limited ability of teachers and the lack of learning resources for teachers so that the implementation in several schools has not been implemented and is not running effectively and efficiently, so teachers need reinforcement in the form of training. This study aims to see the effect of performance-based cultural arts practice assessments training for arts and culture teachers. The training was carried out in a limited with a small sample of 5 art and culture teachers from SMKN 1, SMKN 2, SMKN 3, SMK Bhakti Nusantara Salatiga. The research used quantitative research with a pre-experimental of One Group Pretest Posttest Design with data collection techniques in the form of interviews, documentation studies and tests. Interviews and documentation studies were conducted to analyze the needs of the training carried out. The test used to measure the teacher's understanding and knowledge of material by giving a pretest and posttest. The data analysis technique was processed by quantitative descriptive techniques by conducting the Normality Test and the Paired Samples T-Test. The results showed that the value of sig. (2-tailed) is 0.012 (&lt; 0.050), meaning that H0 is rejected and Ha is accepted. Therefore, it can be said that there is an increase in competence between before and after the training is carried out.
Correction to: The Mind-Technology Problem

The book was inadvertently published with errors in Chapter 1 and Chapter 13.
Scaling Graph Propagation Kernels for Predictive Learning

Many real-world applications deal with data that have an underlying graph structure associated with it. To perform downstream analysis on such data, it is crucial to capture relational information of nodes over their expanded neighborhood efficiently. Herein, we focus on the problem of Collective Classification (CC) for assigning labels to unlabeled nodes. Most deep learning models for CC heavily rely on differentiable variants of Weisfeiler-Lehman (WL) kernels. However, due to current computing architectures' limitations, WL kernels and their differentiable variants are limited in their ability to capture useful relational information only over a small expanded neighborhood of a node. To address this concern, we propose the framework, I-HOP, that couples differentiable kernels with an iterative inference mechanism to scale to larger neighborhoods. I-HOP scales differentiable graph kernels to capture and summarize information from a larger neighborhood in each iteration by leveraging a historical neighborhood summary obtained in the previous iteration. This recursive nature of I-HOP provides an exponential reduction in time and space complexity over straightforward differentiable graph kernels. Additionally, we point out a limitation of WL kernels where the node's original information is decayed exponentially with an increase in neighborhood size and provide a solution to address it. Finally, extensive evaluation across 11 datasets showcases the improved results and robustness of our proposed iterative framework, I-HOP.
Rapid circle detection through fusion of summative statistics of edge components

Circle detection of edge images can involve significant time and memory requirements, particularly if the circles have unknown radii over a large range.We describe an algorithm that processes an edge image in a single linear pass, compiling statistics of connected components that can be used by two distinct least square methods.Because the compiled statistics are all sums, these components can then be quickly merged without any further examination of image pixels.Fusing multiple circle detectors allows more powerful circle detection.The resulting algorithm is of linear complexity in the number of image pixels, and quadratic complexity in a much smaller number of cluster statistics.
A Novel Approach for Video Inpainting Using Autoencoders

Inpainting is a task undertaken to fill in damaged or missing parts of an image or video frame, with believable content.The aim of this operation is to realistically complete images or frames of videos for a variety of applications such as conservation and restoration of art, editing images and videos for aesthetic purposes, but might cause malpractices such as evidence tampering.From the image and video editing perspective, inpainting is used mainly in the context of generating content to fill the gaps left after removing a particular object from the image or the video.Video Inpainting, an extension of Image Inpainting, is a much more challenging task due to the constraint added by the time dimension.Several techniques do exist that achieve the task of removing an object from a given video, but they are still in a nascent stage.The major objective of this paper is to study the available approaches of inpainting and propose a solution to the limitations of existing inpainting techniques.After studying existing inpainting techniques, we realized that most of them make use of a ground truth frame to generate plausible results.A 'ground truth' frame is an image without the target object or in other words, an image that provides maximum information about the background, which is then used to fill spaces after object removal.In this paper, we propose an approach where there is no requirement of a 'ground truth' frame, provided that the video has enough contexts available about the background that is to be recreated.We would be using frames from the video in hand, to gather context for the background.As the position of the target object to be removed will vary from one frame to the next, each subsequent frame will reveal the region that was initially behind the object, and provide more information about the background as a whole.Later, we have also discussed the potential limitations of our approach and some workarounds for the same, while showing the direction for further research.
Facial Recognition Using Image Encoding (Alternate Method)

Facial Recognition is a technique implemented in a myriad of ways, but the approach of facial encodings stays predominant. One of these approaches is using “Siamese networks”. The proposed model is inspired by and is an improvement of this approach. The use of Siamese networks is quite standard, but it has some disadvantages, namely high training time, memory overhead, and implementation time. These problems are addressed in this paper. Training the Siamese network can be a huge overhead and the network is most of the time too complex to easily change its architecture. The network provided in this paper removes some of these disadvantages from the Siamese network. Siamese is more computationally expensive. Instead of training a pre-trained network again this alternative method might help reduce the overhead. Implementing the Siamese network in using one of the many technologies is time-consuming as one needs to specify and code the back-propagation as the model itself is too specialized, also the fact that the training is modified makes it less efficient to train the model as many of these libraries contain memory optimizations for many of the standard procedures used but the ones used in Siamese networks are too specialized thus causing memory overhead. The model proposed in this paper is quite straightforward, easy to implement, and thus causes less overhead.
Upper Prımary Students’ Crıtıcal Readıng Skılls in Surakarta: Gender Based Analysıs

This study aims to assess the critical reading skills of upper primary school students in Surakarta, Indonesia. Therefore, descriptive research design was used. The research participants consisted of sixty students (20 male and 40 female) in the fourth, fifth and sixth grade from five public primary schools and five private primary schools.. They were purposively selected from five public schools and five private schools. In terms of gender composition, the number of male students was proportional to the number of female students. . Thirty male students and 30 female students involved in this qualitative research. The data were collected from reading comprehension test and interview. The results were analyzed using Paul &amp; Elder’s (2008) six aspects of critical reading skills which consist of accuracy, clarity, precision, depth, relevance and logic. The results of this study revealed that in terms of accuracy and relevance, private primary school students' critical reading skills were higher than that of the public primary school students, while the same results were achieved for clarity and logic, depth and precision. While the students in the sixth grade developed all aspects of the skills equally to a comprehending level, the fourth graders’ clarity and the fifth graders’ clarity and logic were in the emergent level. In terms of gender, the male students in the fifth grade and the female students in the sixth grade showed a comprehending level in almost all of the aspects.
Speaking Language Words, Terms, and Sentences in Virtual Presentations Bali State Polytechnic Students

Students' ability in spoken or spoken language can be seen in communicating and presenting in public.This study aims to determine the level of use of spoken language in virtual presentations of Bali State Polytechnic students.This is important to do because there is a tendency to use words, terms, and sentences that are not in accordance with applicable rules, such as phonological rules, mentions of terms that tend to use foreign terms.This study uses the observation method, while the technique used is a recording and note-taking technique.From the results of the virtual student presentations, the results showed very good results.This can be seen in the use of words and terms that scored 99.67 and 98.28, respectively, with very good predicates, while the use of effective sentences was still below the standard with an average score of 49.28.In addition, in the presentation process, students quite mastered the material presented, so that the atmosphere of the presentation went quite smoothly, both in substance and in using good and correct Indonesian.Thus, the average value in the arrangement of words, terms, and sentences is 82.48, it can be said that the use of the spoken language of the Bali State Polytechnic students in virtual presentations is quite good.
Using Invertible Plugins in Autoencoders for Fast and Customizable Post-training Optimization

One of the main motivations for modern drug research is the production of new compounds that act as drugs, however developing a new drug is an excessively time and resource intensive process.Deep generative neural networks might provide a solution.With their help, we may be able to search in a continuous latent space to find drug molecules that are not yet known but have suitable chemical and structural properties (e.g.solubility, interaction with a given target protein).In this paper, we propose a model which can generate novel drug candidates, that are suitable for a pre-specified objective function of arbitrary properties.The model consists of a generative network and a predictor.The former is an autoencoder which utilizes attention to handle the textual representation of molecules, while the latter uses matrix factorization to predict drug-target interactions (DTI).With a genetic algorithm we can generate novel compounds from the continuous latent space, but if there are changes in the objective function, we may need to train the whole model again.This problem is typical of conditional generative models, to address it, we separated the predictor from the pretrained autoencoder thus forming the plugin.In addition to getting a flexible architecture without any deterioration in the so far achieved results, our model can also be used in a distributed setup by concatenating the plugins.In this way, the objective function can be broken down to smaller subtasks, which can be solved by different plugins without sharing any data.
Image montage detection based on image segmentation and robust hashing techniques

We present a new method for detecting montages and, in general, recognizing images or parts of images.Image recognition is becoming increasingly important, for example, in detecting copyright infringement, disinformation that puts images in a different context, detecting child pornography in image collections.Numerous methods based on robust hashing and feature extraction, more recently also supported by machine learning, are already known for this purpose.Inverse image search solutions for users are also available here.In general, however, these methods are either only robust to a limited extent against changes such as rotation and cropping or they require a high data and computational effort.Especially when several images are copied into one another and montages are created, automated recognition has been difficult to achieve up to now.
Sulfur and lead isotope geochemical characteristics of Pb-Zn deposits in the Khau Loc zone, northeastern Vietnam, and their significance

In northeastern Vietnam, the Khau Loc zone is considered to have high potential for lead-zinc mineralization. The lead isotope data for 18 galena samples and 18 ones of δ34S isotope data (including galena and pyrite samples) were collected from lead-zinc ore deposits in some areas in the Khau Loc zone, including Phia Dam, Khuoi Man, Ban Lin, Lung Dam, and Ta Pan. These were employed to investigate the sulfur and lead isotope geochemical characteristics of Pb-Zn deposits and their significance in this study. The samples were analyzed using the LA-ICP-MS to show that the Pb isotopic ratios of 206Pb/204Pb, 207Pb/204Pb, and 208Pb/204Pb in the galena samples range from 17.8908 to 18.6012, 15.5794 to 16.1025, 38.4420 to 39.2118, with the average values of 18.296, 15.749, and 38.812, respectively. The pyrite and galena samples had the δ34S isotope, ranging from 9.0 to 15.106. The sulfur isotope systematics implies that most of the lead-zinc ore formations originated from marine sedimentary evaporation deposits and magmatic intrusion-volcanic eruption sources rich in silica. The distribution of lead isotopic ratios had a well-defined cluster for each deposit, indicating the formation of lead-zinc deposits and lower crust and orogen trends. In addition, these findings of lead isotopic ratios and δ 34S isotopes proved that the Khau Loc zone is an activated structure with continuous growth in continental crust thickness during the early Proterozoic and Cenozoic periods. Furthermore, the study results also presented the evolution of material sources involved in the formation of lead-zinc ores in the Khau Loc zone.
USING COOPERATIVE LERNING MODEL- SNOWBALL THROW TO IMPROVE STUDENTS ENGLISH LEARNING OUTCOMES

The goal of this study was to see if a snowball throwing cooperative learning strategy could improve students' English learning outcomes in from of writing an advertisement. Classroom Action Research is the research method used in this study. The actions are divided into two cycles, each with four stages: preparation, implementation, observation, and reflection. The study was carried out at SMPIT Al Muhsinin with 24 students, 10 males and 14 females. Data gathering procedures are observations, interviews, assessments, and documentation. the findings of the research shows that snowball throwing cooperative learning strategy has a good influence on enhancing student learning outcomes, as seen by an increase in student learning completion in each cycle, which is 56.25 percent in cycle I and 81.25 percent in cycle II. As a result, the classical completion of pupil learning has been attained. The Snowball Throwing methodology, when used collaboratively, can boost students' learning motivation and cooperation when learning English.
QUANTUM JOURNALISM: PROLEGOMEN OF MEASUREMENT (identification of criteria for the formation of representation about the unit of analysis and the unit of measurement)

The article aimed to search for and identify the criteria for forming an idea of the unit of analysis and the unit of measurement in quantum journalism (Kyushu).The research methodology involved the use of methods of three groups: general philosophical (the method of quantum monism; the ideas of realism; the concept of Unity); scientific-practical methods –observation, description and measurement; scientific theoretical methods –formalization, axiomatization, analysis and synthesis, deduction and induction, generalization, analogy, and abstraction.Results. Since today in the philosophical fields (metaphysics, nonclassical physics (quantum), and classical physics) there are no units of analysis and measurement of synergetic processes and phenomena in quantum journalism (quantum communication), further within holism and the author's concept of Unity it is proposed to create a new "1 hall", or "one holism". The range of analysis and measurement that form the unit "1 hall" should be considered the manifestations of the impact on the environment of a portion of energy (quantum) in the form of intensity and strength of changes that such energy (quantum) causes information flow.Conclusions. According to the results of the analytical review of existing ideas on measurement, it is appropriate to state ambivalent tendencies to identify the criteria for forming an idea of the unit of analysis and the unit of measurement in quantum journalism (more broadly -in the theory of quantum communication). On the one hand, measurement in quantum journalism is inexpedient. On the other hand, such a measurement is possible. From the standpoint of materialism, measurement in quantum journalism is possible thanks to digital indicators. From the point of view of metaphysics, measurement is possible taking into account the synergetic unity as a result of the combination of synergetic-convergent and cross-transmedia characteristics of information processes due to the unit "hall" (holism).Key words: quantum journalism, kyuzhur, measurement, unit of analysis, unit of measurement, identification of criteria.
A STUDY ON THE CHALLENGES FACE BY TEACHERS IN TEACHING ENGLISH IN MULTILINGUAL CLASSROOM AT SECONDARY LEVEL IN PUBLIC SCHOOLS OF LIAQUATABAD TOWN KARACHI

English as a second linguistic language generates a challenging charge on its teaching, specifically in those areas where its exposure is limited. This research tried to examine English teaching challenges met by the teachers in bilingual classrooms at the public school of liaqatabad Karachi. Students who go through public school interact in different languages. With the help of this existing research, we aimed to sort out the challenges and difficulties faced by the teachers of secondary school during the period of teaching English in the classroom of a multilingual setting. Random sampling was used and 30 public sector Secondary school teachers have participated in the study. For data collection, we used a questionnaire. The data were analyzed by using the simple percentage frequency method. Findings of research revealed that there were lots of difficulties faced by teachers in the bilingual classroom. The student in the multilingual classroom needs to apply the English language since they are surprised whether or not to commit mistakes. The curriculum strength is improper for supplementary students with improving their English competence in the multilingual classroom. Code-exchanging is utilized by the instructor to teach the students. The study suggests that; the teacher capacity be prepared to adopt new methodologies to overcome challenges in multilingual classrooms
Rancang Bangun Aplikasi Laporan Keuangan Berbasis Web Pada Pt. Anugrah Putra Kharisma

&#x0D; Anugrah Putra Kharisma is a company that carries out the business of buying land, building houses to selling houses. To support this business, one of the activities at PT. Anugrah Putra Kharisma is managing the company's financial data by making financial reports in the form of income and expense reports. The problem is that so far the preparation of financial reports takes a long time because every transaction is recorded in the books by the Administration Section. Furthermore, the transaction data is entered and processed with the Microsoft Excel application. This causes the process of making financial statements takes a long time. Based on these problems, the solution offered in this study is to design a web-based financial statement application at PT Anugrah Putra Kharisma. This financial report application consists of managing daily financial reports, monthly financial reports, annual financial reports, and printing reports. By utilizing the application of financial statements can help companies to solve existing problems.&#x0D;
Research on model mechanism of B2B transaction based on delivery means of blockchain

The security of customer information, business information and payment information pool is a problem in the process of transaction payment under traditional B2B e-commerce mode.To solve this security problem, a B2B e-commerce transaction payment mode based on block chain technology is constructed.This study integrates the technical characteristics of decentralisation in blockchain algorithm, point-to-point distributed computing network, distributed storage of data and security and credibility of data encryption into the system architecture of B2B e-commerce transaction payment, and explores the feasibility of blockchain payment model architecture from the perspective of demand and supply of system products, then a secure payment model mechanism based on blockchain technology is constructed, which provides an effective model architecture solution to solve the problems of payment security and information security in the traditional B2B e-commerce transaction payment system.
Performance comparison between fixed tilt angle and solar tracking systems at Basra governorate: A case study

Theoretical &lt;span lang="EN-US"&gt;calculations and online system simulations using PVWatts and global solar atlas simulators, were conducted in this study to find the difference in solar power production between fixed solar power systems and tracking systems at Basra Governorate. The research included the analysis of geographical location and weather conditions and their effect on output power. The reliant power resource types and power generation of the southern region of Iraq as well as load demands were demonstrated and discussed in this research. Furthermore, the sun path, solar angles and solar radiations were considered in this study, in addition to the mathematical calculations of optimum tilt angles. The methodology used in this study was based upon theoretical and online measures of real-time weather factors, solar angles, solar radiations and model properties of the examined system. The results and factors of different systems including: peak sun hours per day, dc to ac derate factors, tilt angles, solar radiations and power production were compared to multiple similar research elements that were accomplished around the same region and some other countries. The study concluded that solar tracking system absorbs more radiations and produces an annual production of 15–30% higher than fixed tilt angle system.&lt;/span&gt;