Reviewerly/exHarmony huggingface dataset:
A Data-Driven Method for Estimating Behind-the-Meter Photovoltaic Generation in Hawaii

Due to the increasing penetration of distributed behind-the-meter photovoltaic (PV) systems and the installed utility revenue metering limited to monitoring only the net power import/export of the household, it is increasingly challenging for utilities to effectively plan and operate the grid. This paper proposes a methodology that estimates behind-the-meter PV generation using a selected subset of monitored PV systems. It is a data-driven approach, and the PV output is estimated utilizing a statistic regression model. A Minimum Redundancy Maximum Relevance (MRMR) algorithm is applied to preselect the optimal subset of the monitored PV systems. The performance of this approach is compared with a spatial interpolation method and a model-based approach. The proposed method is validated using high-resolution meter data recorded from 18 residential rooftop PV systems located on the island of Maui, Hawaii.
Smart-освіта як складова сучасного суспільства

International scientific and practical conference «Pedagogy and Psychology in the Modern World: the art of teaching and learning» : conference proceedings, February 26–27, 2021. Riga, Latvia : «Baltija Publishing». 444 pages.
A Study on the Grammar Difficulty of the Chinese Language Exam to the College Scholastic Ability Test(CSAT) from 2009 to 2018

This research analyzed 51 grammar points in the 46 grammar questions among the ‘Chinese Language Exam of the College Scholastic Ability Test(CSAT)’ from 2009 to 2018.<BR> The theory we used is the Grammar Difficulty level of Park Yong-jin(2019), who modified the Hierarchy of Difficulty of Porter(1967). The analysis results are as follows.<BR> (1) Difficulty level 0: 2 grammar items; (2) Difficulty level 1: 3 grammar items; (3) Difficulty level 3: 25 grammar items; (4) Difficulty level 4: 8 grammar items; (5) Difficulty level 5:13 grammar items<BR> High school Chinese class has 85 hours in total. We should consider whether high school students can learn Chinese grammar level of HSK level 3 in high school Chinese class. And there were 13 grammatical items in Level 5 of grammar difficulty. Our analysis shows that overall Chinese test question of CSAT were difficult for high school students. As for the difficulty level, we have not set up comparisons with other foreign languages. Therefore, there will have to be other analyses as to why the current Chinese test is so difficult.<BR> We hope our analysis will be a good evidence to judge which grammar items are easy for learners and which are difficult objectively. And we also hope that our analysis will be a good source of evidence for textbook editing, and curriculum strategy.
PENGEMBANGAN KAWASAN PESANTREN MODERN RAUDHATUL ULUM MERANTI

Raudhatul Ulum Meranti Islamic Boarding School is a da'wah institution that was established to educate the generation of Muslims in Indonesia, especially in West Kalimantan. Raudhatul Ulum Meranti Islamic Boarding School was founded in 1896 in a village called Meranti Village, Sungai Ambawang District, Kubu Raya Regency. The curriculum applied by the pesantren initially only adhered to the classical system (teaching the yellow book) and developed into a curriculum sourced from the Ministry of Religion (KEMENAG). The aim of developing the area of Raudhatul Ulum Meranti Islamic Boarding School is to make facilities suitable for the modern education system. The design location is on Jalan Muhajirin, Kampung Meranti, Puguk Village, Sungai Ambawang District, Kubu Raya Regency. The stage method in this design starts from the Idea Stage, Data Collection, Analysis, Synthesis, Pre-Design and Design Development. The concept of Natural Pro Rate is applied so the areas that are still green do not have to build by destroying nature in the area, but rather organize and maintain the natural conditions in order to remain green. The results of the development design at Raudhatul Ulum Meranti Islamic Boarding School can make the mosque building as the heart of the area. Worship and educational facilities are made with Islamic nuances by combining ornaments in the building and creating a separate area between the male and female students.
Model-Free Approaches

In the previous chapter, we looked at dynamic programming where we knew the model dynamics p(s’, r| s, a), and this knowledge was used to “plan” the optimal actions. This is also known as the planning problem. In this chapter, we will shift our focus and look at learning problems, i.e., a setup where the model dynamics are not known. We will learn value and action-value functions by sampling, i.e., collecting experience by following some policy in the real world or by running the agent through a policy in simulation. There is another class of problems where we find the model-free approach more applicable. In some problems, it is easier to sample than to calculate the transition dynamics, e.g., consider solving a problem of finding the best policy to play a game like blackjack. There are many combinations to reach a score that depend on the cards seen so far and the cards still in the deck. It is almost impossible to calculate the exact transition probabilities from one state to another state but easy to sample states from an environment. To summarize, we use model-free methods when either we do not know the model dynamics or we know the model, but it is much more practical to sample than to calculate the transition dynamics.
How to Restore Accidentally Deleted Bookmarks on Chrome

Deleting things help us make room for new stuff. Nonetheless, deletion can become painful sometimes. As an internet user, you know what a bookmark is. ...
Deep Learning and Traffic Classification: Lessons learned from a commercial-grade dataset with hundreds of encrypted and zero-day applications

The increasing success of Machine Learning (ML) and Deep Learning (DL) has recently re-sparked interest towards traffic classification. While classification of known traffic is a well investigated subject with supervised classification tools (such as ML and DL models) are known to provide satisfactory performance, detection of unknown (or zero-day) traffic is more challenging and typically handled by unsupervised techniques (such as clustering algorithms). In this paper, we share our experience on a commercial-grade DL traffic classification engine that is able to (i) identify known applications from encrypted traffic, as well as (ii) handle unknown zero-day applications. In particular, our contribution for (i) is to perform a thorough assessment of state of the art traffic classifiers in commercial-grade settings comprising few thousands of very fine grained application labels, as opposite to the few tens of classes generally targeted in academic evaluations. Additionally, we contribute to the problem of (ii) detection of zero-day applications by proposing a novel technique, tailored for DL models, that is significantly more accurate and light-weight than the state of the art. Summarizing our main findings, we gather that (i) while ML and DL models are both equally able to provide satisfactory solution for classification of known traffic, however (ii) the non-linear feature extraction process of the DL backbone provides sizeable advantages for the detection of unknown classes.
The Semantic Differences between There’s and There are Selections Based on Types

The use of the contraction ‘There"s’ and the non-contraction ‘There are’ in There Construction(TC) is a problem that is not solved by syntactic explanations. ‘There"s" is an automatic utterance. Nevertheless, choosing "There are" depends on the speaker"s choice according to context. In this paper, we have presented some examples of the choices of ‘There"s" and ‘There are" to prove this. The contraction ‘There"s’ is selected in a situation where the topic is shared through such as visual effect or use of the adverbial phrase, the list function of TC and its function to remind. However, in a situation where the topic is not shared at all, and a situation where careful consideration is required, the possibility of choosing ‘There are" is increased. In addition, the choice of two types may vary depending on the speaker"s intention, perception or cognition on the noun phrase to be placed in the Associate. In this study, We suggested that there may be functional or semantic differences in the choices between ‘There"s’ and ‘There are’. And the goal of this study is to suggest that a detailed pragmatic approach to the selection of the contraction ‘There"s’ and the non-contraction ‘There are’ is necessary and to lay the foundations for the follow-up study.
Clustering Students and Inferring Skill Set Profiles with Skill Hierarchies

Cognitive diagnosis models (CDMs) are a popular tool for assessing students' mastery of sets of skills. Given a set of $K$ skills tested on an assessment, students are classified into one of $2^K$ latent skill set profiles that represent whether they have mastered each skill or not. Traditional approaches to estimating these profiles are computationally intensive and become infeasible on large datasets. Instead, proxy skill estimates can be generated from the observed responses and then clustered, and these clusters can be assigned to different profiles. Building on previous work, we consider how to optimally perform this clustering when not all $2^K$ profiles are possible, e.g. because of hierarchical relationships among the skills, and when not all possible profiles are present in the population. We compare hierarchical clustering and several k-means variants, including semisupervised clustering using simulated student responses. The empty k-means algorithm paired with a novel method for generating starting centers yields the best overall performance.
InfoGuides: Leganto - Course Reserves: Introduction

Instruction and guidance for Faculty and Staff for using Leganto in Blackboard to manage their e-reserves George Mason University will be using the ExLibris product Leganto to manage e-reserves in courses. This tool called (placeholder) will be available inside Blackboard for our Faculty and Staff to bring a more direct means of creating and carrying over li
Economic Benefits of Implementing Cloud in Higher Education Institutions, a reflection

Most of the organisations have deployed communication and information systems that provide them seamless connectivity with partners and branches, and control on the resources, resulting in efficiency, easy management, time saving and enhanced productivity. As information and communication systems are becoming part and parcel of organisations without which modern enterprises cannot even think of existence, their reliability, security and cost effectiveness are some major concerns for enterprises to deal with. The adoption of cloud computing had been a revolutionary milestone in this regard. Higher education institutions have also benefited from cloud implementations. The cloud implementations in higher education in Sultanate of Oman although being abysmally low has a gradual shift towards cloud hosting and implementation of clouds in higher education institutions. This research is a mere effort to highlight the economic benefits that higher education establishments can achieve by the implementation of cloud computing.
IoT Solutions Industry Prospects Analysiswith Specific Reference to Mobiloitte Inc

Life is made easy by a rising technology, the Internet of Things, which promisedtransformation in the way we work, we live, we play, we analyze and we think. Theinfluence of IoT is seen everywhere today, from consumer products to military equipment,from motorbikes to airplanes, from manufacturing units to industries, and from daily useitems to utility components and from house to smart cities. The everyday use objects whichare being combined with Internet connection and data analytics capabilities guarantee ease ofdoing work, ease of living, ease of analyzing, ease of thinking and ease of playing. Inessence, IoT provides a flat-form to interconnect various electronic devices through theInternet and open up a new world of possibilities. Mobiloitte is a leading complete servicesolution development company for IoT, AI, and BOTS along with other related areas withtime, security, scale and performance as its focus points. The company strives for 'Top NotchQuality Work' and 'Complete Customer Satisfaction' as its business ethics. E3 – Experience,Excellence, and Exuberance is the company's work motto for the 'Go-to-Market Strategy' ofthe company to provide unique services and solutions to its customers and by that keepingitself in advantage position in the field competition. The company is equally comfortableworking with different types of setups like Start-Ups, Small & Medium Enterprises, LargeEnterprises, Development Sector, Public-Private Partnerships, and Governments.Completion of more than 5000 projects in a decade is a testimony to that. In this paper, weattempted to analyze various IoT solutions the company provides, highlight their technicalbackgrounds and list out their applications. At present, the company is providing IoTsolutions in a large spectrum covering areas like surveillance, power, video inspection,customer feedback, marketing, skill-building, security, etc. Besides, this article alsodeliberates business challenges and potential solutions to provide different IoT basedsolutions appropriate to customer requirements and lists out emerging IoT technologies witha futuristic outline.
Comparative analysis of Median filter family for Removing High-Density Noise in Magnetic Resonance Images

Magnetic Resonance Imaging (MRI) is a medical indicative test utilized for taking images of the tissue points of interest of the human body. During image acquisition, MRI images can be damaged by many noise signals such as impulse noise. One reason for this noise may be a sharp or sudden disturbance in the image signal. The removal of impulse noise is one of the real difficulties. As of late, numerous image de-noising methods were produced for removing the impulse noise from images. Comparative analysis of known and modern methods of median filter family is presented in this paper. These filters can be categorized as follows: Standard Median Filter; Adaptive Median Filter; Progressive Switching Median Filter; Noise Adaptive Fuzzy Switching Median Filter; and Different Applied Median Filter. The de-noising technique performance for each one is evaluated and compared using Peak Signal Noise Ratio, Structural Similarity index Metric, and Beta metric as quantitative metrics. The experimental results showed that the latest de-noising technique, Different Applied Median Filter (DAMF), produced better results in removing impulse noise compared with the other de-noising techniques. However, this filter produced de-noised image with nonlinear edges in high-density noise. As a result, noise removal from images is one of the low-level images processing which is considered as a first step in many image applications. Therefore, the efficiency of any image processed depends on the efficiency of noise removal technique.
Parthenope: A Robotic Musical Siren

Parthenope is a robotic musical siren developed to produce unique timbres and sonic gestures. Parthenope uses perforated spinning disks through which air is directed to produce sound. Computer-control of disk speed and air flow in conjunction with a variety of nozzles allow pitches to be precisely produced at different volumes. The instrument is controlled via Open Sound Control (OSC) messages sent over an ethernet connection and can interface with common DAWs and physical controllers. Parthenope is capable of microtonal tuning, portamenti, rapid and precise articulation (and thus complex rhythms), and distinct timbres that result from its aerophonic character. It occupies a unique place among robotic musical instruments.
Application and Satisfaction Study of Medua-Based TEACHING & LEARNING Method in Beauty Education: Focusing on Flipped Learning using Google Classroom

Purpose: After the 4th Industrial Revolution, changes in innovation are required in education. With a report by technology company, Dell estimating that 85 percent of jobs that will exist in 2030 haven’t yet been in-vented, today’s school leavers are facing a future in an uncertain job market. Find out how schools are helping students to develop skills that will make them work-ready. This researcher applied media-based teaching and learning methods to provide classes to beauty major students. Method: As a result of the survey, most of the students were satisfied with the medium-based teaching and learning method for flipped learning using Google classroom. The following is a summary of what students are satisfied with in the Google classroom and Flipped Learning class. The students responded that they were able to have fun classes without being bored, received a lot of help from the professor, were able to repeat learning at home, check the contents of the assignments correctly, and concentrate well. Students pointed out that it was a little difficult to use at first, and that they had to download class-related apps as an inconvenience during class. Results: As a result of the survey, most students were satisfied with the class using media-based teaching and learning methods. The contents that were good for teaching using the media-based teaching and learning method are summarized as follows. “It was great to be able to have more fun classes”, “I received a lot of help from the professor”, “I can study at home”, “I was able to check exactly what the assignment was”, “It is possi-ble to repeat learning”, “It wasn t boring. and I was able to concentrate well”. The inconvenient points in class were “It was a little difficult to use for the first time”, “Internet data is essential”, “You need to download a class-related app”. Conclusion: To transform future education, the ability of media-based teaching and learning methods using digital skills is essential for both instructors and learners. For this, the foundation should be actively formed to study the effectiveness and application of media-based education such as infrastructure configuration and op-eration management, various content development and support, and digital skills.
Early Diagnosis of Sinusitis Using Expert System Methods: Early Diagnosis of Sinusitis Using Expert System Methods

Sinusitis is a disease of the nose, which occurs due to inflammation of the sinuses due to allergies or infection with viruses, bacteria or fungi. Sinusitis can occur in any of the four sinuses (maxillary, etmoidalis, frontalis, sphenoidalis). The most common causes of sinusitis are due to viral infections. Often times it is caused by a cold or flu virus that is spread by the sinuses from the upper respiratory tract. After a cold or flu, secondary bacterial infection can occur. This will cause the walls of the sins to become inflamed or inflamed. An infected tooth can also make the sinuses infected. A doctor can diagnose sinusitis by looking at the symptoms that occur. For example, nasal congestion or runny nose with facial pain. If the sinusitis is severe or recurs, You are advised to see an ENT specialist (ear, nose, throat). These specialists will try to find the main cause of sinusitis that occurs. CT scans can also be used to find out the cause of sinusitis. Therefore, an expert system application was made using the forward chainy method to diagnose sinusitis. This system application is a system that helps doctors (experts) and the public in diagnosing sinusitis with symptoms felt by users. an expert system application was made using the forward chainy method to diagnose sinusitis. This system application is a system that helps doctors (experts) and the public in diagnosing sinusitis with symptoms felt by users. an expert system application was made using the forward chainy method to diagnose sinusitis. This system application is a system that helps doctors (experts) and the public in diagnosing sinusitis with symptoms felt by users
Strategic Planning on Smart Mobility Development

The increase in population and in vehicles has generated a challenge in urban transportation. Simultaneously, Intelligent Transport System (ITS) technology development has provided urban areas with an opportunity to address transportation challenges. Therefore, a concept of smart mobility is developed, which is derived from smart city concept using ITS development. The objective of research is to organize a Strategic Planning of Smart Mobility. This research used the qualitative descriptive approach. Its data were collected from the city of Surakarta as an implementer of Smart Mobility through in-depth interviewing and content analysis. Data analysis in the first stage was carried out by using the SWOT analysis method to determine strategic issues. The second stage of analysis was aimed to evaluate the strategy by using the litmus test. The results of this research based on the two stages show that strategic plan could be observed from the development of Smart Mobility in Surakarta City and several strategies could be offered and formulated as follows: 1) strategy of developing and improving cooperation with stakeholders; 2) strategy of improving and intensifying the application of e-Gov through ITS application and development; 3) strategy of reinforcing inter-mode integration; and 4) strategy of developing the synchronization of public policy to restrict the number of private vehicles.
EFFECTIVE TECHNOLOGIES FOR TEACHING STUDENTS DURING THE COVID PERIOD

I. Balandina , L. Uzdova , T. Moskvitina , E. Nikitina, G. Shiganova , K. Shishkina South Ural State Humanitarian Pedagogical University (RUSSIAN FEDERATION)
THE RELATIONSHIP BETWEEN STUDENTS’ PERSONALITY AND SPEAKING PERFORMANCE

The purpose of this research is to find the relationship between extrovert and introvert personality and speaking performance of students in class XI Imam Bukhori SMK IT Multimedia An-Nuqthah, Tangerang, Banten. This research method is used as a quantitative correlation study. The population and sample are 21 students of SMK IT Multimedia An-Nuqthah, using simple random sampling in class. A questionnaire is used to determine the student’s personality type, and a test is used to determine the student’s speaking performance. The personality questionnaire and the speaking test scores are correlated by using the Pearson product moment formula. The result of  is higher than  in 5% (0, 9984 > 0, 4329) and 1% (0, 9984 > 0, 5487). The conclusion of this research there is the relationship between students' personality and speaking performance. It is hoped that this research will help achieve goals and success, and also help to be more effective in the process of English teaching. Keywords : personality, extrovert, introvert, speaking
Comparative Analysis of Accuracy in Identifying Types of Glass

To see whether the proposed research model is able to improve the performance of the classification of the Glass Type Identification data using the K-Nearest Neighbor (K-NN) method then the results will be compared with the C4.5 method and the Naive Bayes method, a performance analysis of the methods will be carried out. The results are based on the results of the Confusion Matrix tabulation (two-class prediction. In this study, only three preprocessing processes were carried out. The first process is handling missing value. The missing value for attributes with numeric values is replaced by the mean (mean) value of the attributes in the same column. Meanwhile, the missing values for attributes with nominal values are replaced by the most likely values for the attributes in the same column. Then the second process is the handling of duplicated data. The data recorded were 214 data, the number of attributes was 9 attributes and the number of classes was 6 classes.The results of this study show that the highest accuracy value is in the C4.5 method with an accuracy of 73.45% with a value of K = 2 and an error rate of 26.55%, while the method with low accuracy is the KNN method. with an accuracy value of 61.95% and an error rate of 38.05%. Naive Bayes has an accuracy of 63.33% and an error rate of 36.67. Therefore C4.5 is more effective than the two methods.