Reviewerly/exHarmony huggingface dataset:
Efektivitas Pembelajaran Daring Matematika Menggunakan Google Classroom Selama Pandemi Covid -19

This study aims to determine the effectiveness of online learning using google classrooms during the Covid-19 pandemic in the Mathematics subject focusing on trigonometric equations in class XI MIPA SMA Negeri 1 Selong. This research is quantitative descriptive. The population in this study were all class XI MIPA taught using google classroom. The research sample was selected using cluster random sampling technique, namely class XI MIPA 1 and XI MIPA 2 measuring 70 students. The data collection technique used was the provision of post-test and questionnaire distribution after the students were treated. The research indicator, namely online learning using google classroom, is said to be effective if the student learning outcomes with a percentage of classical completeness ≥85% and student responses are positive to online learning using google classroom. Based on the results of descriptive statistics, if seen from the classical completeness, it was obtained that 60 students were said to have completed their learning or equal to 85,71%, 10 students who did not complete their studies or equal to 14,29% and seen from the students responses to online learning using google classroom there were 11 students who responded very positive or equal to 15,71%, 57 students responded positively or equal to 81,43%, 2 students responded negatively or equal to 2,86%, and no students responded very negatively. Based on the results of the research, online learning using google classroom was effective during the covid-19 pandemic in class XI MIPA SMA Negeri 1 Selong in the 2020/2021 school year.
LibGuides: Basic Academic Research: Home

This LibGuide covers skills, strategies, and materials employed in basic academic research: the sorts of assignments often given to lower division (freshman and sophomore) students in the first two years of college.
Feature Extraction Using Principal Component Analysis (PCA) With Naïve Bayes Classifiers on Twitter Dataset

Performing Sentiment Analysis on Twitter is complicated than doing it for large reviews. This is because the tweets are very short and mostly contain slangs, emoticons, hash tags and other twitter language. Feature extraction is the way toward building a feature vector from a given tweet. Every section in a feature vector is an integer that has a commitment on ascribing a supposition class to a tweet. The cycle of feature extraction is to remove the specific features to improve the accuracy of the classification model. In this paper we proposed Term Frequency-Inverse Document Frequency (TF-IDF) technique is to consolidate Principal Component Analysis (PCA) with Naive Bayes Classifiers. For the classification work, the work proposed could create discrete factors from nonstop esteemed features from the Twitter dataset.
Penerapan Metode Penemuan Terbimbing dalam Peningkatan Pemahaman Konsep Diagram Batang di Kelas IV SDN Karangtengah 1 Kota Blitar

Abstract. Mathematics education in elementary school is the beginning of a child's beginning to explore his ability to understand concepts in mathematics and the knowledge gained will greatly influence him at the next level of education. In learning to make a bar chart in Class IV Semester 2 of SDN Karangtengah 1, Sanawetan District, Blitar City, in the 2020/2021 academic year, it can be seen that there are still many students who do not understand the concept. This is due to the frequent online learning during the corona pandemic, so teachers have not yet completed learning. Such conditions require teachers to conduct research. The research used is a qualitative research on learning Mathematics with the type of Classroom Action Research (CAR). Data analysis techniques used are data reduction, data presentation, and drawing conclusions. The method used to solve problems in learning to make Bar Charts is the Guided Discovery method, which is a technique or method used by the teacher to teach in front of the class, where the teacher divides the task of researching a problem into the class.
Design of printed circuit board detection with image information technology

Abstract In this research, an automatic PCB’s deffects checking tool will be made with image processing technology that adopts Haar Cascade Classifier method as a decision maker for whether or not a broken circuit on the PCB, with this technology the PCB will be detected using a square feature to show the broken path. will be displayed on the interface on the monitor. From the results of the test, data using the Haar Casscade Classifier method has the average percentage of successful detection of broken paths on the PCB at a camera distance of 26 cm and 16 cm is 52.49% with the maximum hassle obtained when the camera distance is placed at a distance of 26 cm and an angle position of 105 degrees which has a success rate of 97.5%. This method is good enough for PCB defect detection tools.
LibGuides: LSP Systems Support: Communication Channels

LSP Systems Support LibGuide: information on system updates, projects, and reporting forms Information on the LSP systems mailing list, a list of vendor service issue pages to sign up for, and information on how to contact the Network Zone Manager.
Color contamination matrix property assessment for improvement of colored smoke PIV

A single-camera color PIV system that can acquire PIV data of three separated layers has been redesigned, purposing improvement of wind tunnel applicability. We target smoke image that has particle-per-pixel values higher than unity. The system constitutes of a high-power color-coding illuminator and a digital color high-speed video camera. RGB values in recorded image involves severe color contaminations due to five optical and digital sequences (Fig. 1). To quantify this, a snapshot calibration is proposed to describe the contamination matrix equation (Eq. (1)). Taking the inverse matrix (Eq. (2)) allows in-plane PIV in each color layer to be accurately implemented. We also derive mathematical limits to operate the colored smoke PIV, which is explained by the matrix property (Eq (3)). Feasibility of the proposed method has been demonstrated by application to a turbulent wake behind a Delta wing (Fig. 2) and also to a boundary layer flow along heated chocolate.
Super-resolution PIV using multi-frame displacement information

High-resolution (HR) fluid-flow velocity information is important to reliably analyze fluid measurements in particle image velocimetry (PIV), such as the boundary layer and turbulent flow. Efforts in PIV to enhance the resolution of flow fields are mainly based on single-frame information, which follows the velocity field estimation and may influence the final reconstruction accuracy. In this study, we propose a novel super-resolution (SR) reconstruction technology from another perspective, which consists of two parts: a multi-frame imaging system and a Bayesian-based multi-frame SR reconstruction algorithm. First, a splitbased imaging system is developed to obtain particle image pairs with fixed displacements. Subsequently, we present a Bayesian-based multi-frame SR (BMFSR) reconstruction algorithm to obtain an SR particle image. Multi-frame particle images collected by the developed system are used as the input low-resolution images for the following novel SR reconstruction algorithm. Synthetic and experimental particle images have been tested to verify the performance of the proposed technology, and the results are compared with the traditional and advanced reconstruction methods in PIV. The results and comparisons show that the proposed technology successfully achieves good performance in obtaining finer particle images and a more accurate velocity field.
SMART TROLLY DESIGN BASED ON MARKER DETECTION

In this modern era, robots are very instrumental in helping the human work and even replace their work. From the various human works, humans will need a trolley to carry goods. As in supermarkets, people will need a trolley to make it easier to carry groceries and other luggage. But with a trolley that is commonly used, users must encourage the trolley to move so that it reduces hand activity to do other activities. Therefore, we need a trolley that can move to follow the user automatically, so the user no longer needs to push the trolley, and the user's hand can be more free to do other activities. This research discusses about trolley robot using marker detection. With the application of this method will help the robot determine the object so as to facilitate the movement of the robot to follow the user. In the testing process carried out in the study, the system accuracy in detecting markers on objects was 70%.
Design Souvenir E-Commerce Application SLB-B Karya Murni Using the Business to Consumer (B2c) Concept

Karya Murni SLB-B School is a school that makes handicrafts and handicrafts in the form of marketing and sales souvenirs which are considered ineffective because the number of products is very large and always increasing, so customers often have to buy product catalogs every month. overcome the above problems so that marketing and sales can be done through the internet without having to buy a catalog every month, and customers only see products and order goods through the website. And the concept of Business to Consumer (B2C) can be used. Karya Murni SLB-B School, marketing still uses catalogs, payments are still made in cash, so customer satisfaction and time are not maximized. To be able to apply the business to consumer concept, sales activities that are open to the public are carried out, information is disseminated to the public, uses public services such as websites, and services must be responsive to consumer demands. To design an E-Commerce application at the Karya Murni SLB-B School, product pages, list, about, contact and login data are accessed by users and members but only members can access product orders and admins can process product data, member data, order data and passwords.
Sistem Informasi Akuntansi dalam Pengeluaran dan Penerimaan Kas pada Dana Bantuan Operasional Sekolah (Bos) di Smk Islam Nurul Ikhwan Selabintana Sukabumi

This study aims to understand the accounting information system in cash receipts and cash disbursements in school operational assistance funds (BOS). The variables used in this study are Accounting Information Systems, Cash Receipts and Cash Expenditures. The method used in this study is a qualitative method by utilizing data collection techniques and then conducting observations, interviews, documentation, triangulation and literature study. The data used in this study is primary data using observations and interviews with the Islamic Vocational School Nurul Ikhwan Selabintana Sukabumi. Where the resource persons in this study were the principal, school committee and BOS treasurer at Nurul Ikhwan Islamic Vocational School Selabintana Sukabumi. Data analysis techniques used are analysis before in the field, analysis during and after in the field, data reduction, data display and drawing conclusions. Based on the results of this study, it shows that the Accounting Information System on the School Operational Assistance (BOS) fund in schools is in accordance with the assistance of an internal control system to be able to produce credible and reliable information and can record errors that have occurred so that they can be corrected therein. there are external controls, administrative controls, operational controls, document controls and security controls. For Cash Receipts on BOS funds used have been based on the technical manual for School Operational Assistance (BOS) funds. In Cash Expenditures on BOS funds, schools have used Regular BOS funds to finance the operational implementation of education in their schools. It can be concluded that the Accounting Information System for Cash Receipts and Expenditures on the School Operational Assistance (BOS) fund is appropriate but there are still shortcomings on the side of the financial statements that are not available.
Environmental Perception with Spatial Regularization Correlation Filter for Visual Tracking

With the introduction of correlation filtering (CF), the performance of visual object tracking is significantly improved. Circular shifts collecting samples is a key component of the CF tracker, and it also causes negative boundary effects. Most trackers add spatial regularization to alleviate boundary effects well. However, these trackers ignore the effect of environmental changes on tracking performance, and the filter discriminates poorly in the background interference. Here, to break these limitations, we propose a new correlation filter model, namely Environmental Perception with Spatial Regularization Correlation Filter for Visual Tracking. Specifically, we use the Average Peak to Correlation Energy (APCE) and the response value error between the two frames together to perceive environmental changes, which adjusts the learning rate to make the template more adaptable to environmental changes. To enhance the discriminatory capability of the filter, we use real background information as negative samples to train the filter model. In addition, the introduction of the regular term destroys the closed solution of CF, and this problem can be effectively solved by the use of the alternating direction method of multipliers (ADMM). Extensive experimental evaluations on three large tracking benchmarks are performed, which demonstrate the good performance of the proposed method over some of the state-of-the-art trackers. • We propose a new framework for visual target tracking that perceives changes in the environment and adaptively adjusts the learning rate to avoid template pollution. Specifically, the APEC indicator and the response error between two frames are used to jointly perceive changes in the environment and adaptively adjust the learning rate. • We uses realistic background information to train filters, which not only suppresses the interference of background information, but also enhances the discrimination ability of the filter. • We solve the energy function of the filter as a non-closed solution. To reduce computational complexity, we use ADMM algorithm to transform the energy function into two subproblems with globally optimal solutions, because both subproblems are convex. Therefore, the two sub-problems have their own closed solution and globally optimal solutions. • Experimental results on three benchmarks, i.e., OTB-2015, TC-128 and VOT-2018 validate that the proposed approach obviously improves the tracking accuracy of CF based trackers.
A New Approach of Image Compression Techniques in Image Processing

In this research work to present the approach for image compression. The different techniques increasing attraction and dependence on the digital photograph have specified increase to that applying visual communication. That approach has to require a huge amount of information in the form of data. For the information, the transformation required less image size. The number of researches has been proposed approach for image compression but that approach destroys the original image quality. To propose an approach for image compression with the help of lossless and lossy.
Study on the supply efficiency of basic public services in counties in underdeveloped areas——Taking Three Gorges Reservoir Area as an example

Enhancing the supply efficiency of basic public services is helpful to improving people ’s livelihoods. It is an effective way to improve the supply level of basic public services and life quality of residents. Taking 15 counties in the Three Gorges Reservoir Area as examples,the three-stage DEA method is used to calculate the supply efficiency of basic public services in the Three Gorges Reservoir Area. The results show that: the overall supply efficiency of basic public services affected by scale efficiency in the Three Gorges Reservoir Area is relatively low,and the low supply efficiency of basic public services could restrain the level and quality of the supply of basic public services. At the same time,it is also influenced by economic development level,financial self-sufficiency,population density,urbanization level and other environmental variables that caused regional heterogeneity in the supply efficiency of basic public services in different counties.
Cybercrime Lawmaking and Human Rights in Ethiopia

Ethiopia has embarked upon an ambitious project of revising a number of laws with a view to entrench human rights and democratic governance. Part of this legal reform program has been the revision of Computer Crime Proclamation No 958/2016. This article examines key aspects of the Draft Computer Crime Proclamation prepared by the Media Law Working Group from a human rights perspective. As it shall be shown in this article, making the cybercrime legal regime human rights friendly has been the overarching objective of the revision project. Most human rights concerns associated with the current cybercrime legislation are, as a result, rectified in the cybercrime Bill. However, the Bill goes overboard in embracing themes that go well beyond the scope of cybercrime legislation. With respect to the overall revision process, the article submits that the process has not been sufficiently inclusive.
ANALYZING STUDENTS’ VOCABULARY BY USING AUDIO LINGUAL METHOD TROUGH FILL-IN-THE-BLANK WORKSHEET SONG

Penelitian ini menggunakan teknik Penelitian tindakan kelas (CAR) tentang efektivitas penggunaan metode audio ligual untuk melatih kemampuan mendengarkan siswa dan menambah kosa kata dengan menggunakan lembarkerja. Subjek penelitian ini adalah siswa kelas delapan SMP Negeri 3 Tabanan pada tahun akademik 2020/2021, yang terdiri dari 20 pria dan 16 wanita. Metode yang digunakan dalam penelitian ini adalah metode penelitian kuantitatif. Data diperoleh dengan menggunakan observasi dan kuisioner. penelitian ini menemukan bahwa hasil post-test disetiap siklus menunjukkan bahwa ada kemajuan yang signifikan dari subjek untuk keterampilan mendengarkan dan menambah kosakata. Penelitian menunjukkan bahwa sebagian besar subjek memberi tanggapan positif tentang penerapan metode audio lingual dengan mendengarkan sebuah lagu melalui. Kesimpulannya, penelitian tindakan kelas ini telah membuktikan bahwa metode audio lingual sangat efektif untuk menambah kosa kata dan melatih kemampuan mendengarkan siswa memalui lembar kerja lagu  pada siswa kelas delapan SMP Negeri 3 Tabanan pada tahun akademik 2020/2021. Selain itu subjek juga merespon secara positif untuk menerapkan metode audio linguial This study is used a Class Action Research (CAR) technique on the effectiveness of using the audio ligual method to train students' listening skills and increase vocabulary by using worksheets. The subjects of this study were eighth grade students of SMP Negeri 3 Tabanan in the 2020/2021 academic year, which consisted of 20 males and 16 females. The method used in this study is a quantitative research method. Data obtained by using observation and questionnaires. This study found that the results of the post-test in each cycle showed that there was a significant progress of the subject for listening skills and adding vocabulary. The study showed that most of the subjects gave positive responses about the application of the audio lingual method by listening to a song. In conclusion, this classroom action research has proven that the audio lingual method is very effective for increasing vocabulary and training students' listening skills through song worksheets for eighth grade students of SMP Negeri 3 Tabanan in academic year 2020/2021. In addition, the subject also responded positively to applying the audio linguial method.
Robustness of the one‐class Peeling method to the Gaussian Kernel Bandwidth

Abstract The One Class Peeling (OCP) method is an outlier detection method for Phase I analysis of large multivariate samples. The two stage OCP method is based on support vector data description and employs the Gaussian kernel function to create sequential flexible boundaries to peel away observations to estimate the center of a data set. Subsequently the distance from that estimated center is used as the monitoring statistic. In this work we study the effect of the bandwidth parameter for the Gaussian Kernel on the performance of the OCP method. We find that the OCP method is robust to the value of the bandwidth parameter in terms of in‐control and out‐of‐control simulation performance. We verify these results on example data. The result is a recommendation for a small value of the bandwidth value, providing a computational advantage to the OCP method.
UX Evaluation Methodology for iTV: Assessing a Natural Language Interaction System

The user experience can be evaluated in different ways, from a combination of approaches and techniques capable of collecting insights about a particular product or system. In the TV ecosystem research field, verifying how users react to new features is an essential step to the integration of functionalities able to enhance the user experience. This is the case of systems based on interaction by natural language (NLI), which have the potential to allow for more simplified navigation (based on conversational dynamics). However, although the spoken interactions are relevant to optimize the consumption of television content, it is essential to identify how they are received and understanded by the user. In this context, this empirical study sought to analyze the experience of using an NLI system controlled by a mobile application. The evaluation was performed employing an open methodology that considers instrumental and non-instrumental qualities of the application, as well as emotional dimensions. This approach was specifically developed for UX analysis of systems and applications related to the TV ecosystem, having recorded positive results in previous studies. In the study here presented, the methodology revealed again to be suitable as it was possible to identify failures and opportunities to improve the assessed NLI system and, finally, to verify that the voice interaction system allowed users a more optimized and accessible experience.
The SelectGen Challenge: Finding the Best Training Samples for Few-Shot Neural Text Generation

We propose a shared task on training instance selection for few-shot neural text generation. Large-scale pretrained language models have led to dramatic improvements in few-shot text generation. Nonetheless, almost all previous work simply applies random sampling to select the few-shot training instances. Little to no attention has been paid to the selection strategies and how they would affect model performance. The study of the selection strategy can help us to (1) make the most use of our annotation budget in downstream tasks and (2) better benchmark few-shot text generative models. We welcome submissions that present their selection strategies and the effects on the generation quality.
Mesin Cuci Tangan Portable Otomatis

Covid-19 is a virus that can adhere to various surfaces of objects. One of the causes of someone contracting the Covid-19 virus is by touching the face, namely the nose and eyes, where the hand has previously touched objects or surfaces that have been infected with the Covid-19 virus. These problems are our advocates for making a portable automatic hand washing machine. This solution is considered important to overcome the spread of the Covid-19 virus through the touch of a hand.In general, the work of the system is to drain water and soap from the faucet automatically and alternately with the trigger is the hand reading by the proximity sensor. The working sequence is water first, then liquid soap, then water again and after that the hands can be dried by means of an automatic hand dryer blower.The hand washing machine that we make is protable and automatic which can be moved easily from one place to another, this allows it to be placed in a room that may be difficult to get to or far from a water source, because in this tool there is a water reservoir.