Reviewerly/exHarmony huggingface dataset:
The Effect of Using SQ4R Technique on Students’ Reading Interest and Reading Comprehension at SMAN 1 Pangkalan Kuras Pelalawan

This research was carried out to find out the categories of students’ interest in reading and reading comprehension and the effect of using SQ4R Technique on their reading interest and reading comprehension at SMAN 1 Pangkalan Kuras Pelalawan. It was done based on a quasi-experimental design that requires a pre-test and post-test for a treated and comparison group. Sample of this research consisted of 76 students that were taken from two classes, namely Class XI IPS 1 as an experimental class (treated group) and Class XI IPS 2 as a control class (comparison group). Data were collected by using and questionnaire and reading comprehension test. SQ4R Technique was used as the treatment for the experimental group. The results indicated that there is a significant effect of implementing the treatment on students’ reading interest in the experimental group. T-test result was -3.4 and its df was 37, by comparing the significant value. If the probability value is &gt; 0.05, the null hypothesis (H0) is accepted. If the probability value &lt; 0.05, the alternative hypothesis (Ha) is accepted. Because the p-value was 0.002&lt;0.05, thus, Ha is accepted while H0 is rejected. In addition, there is a significant effect of using SQ4R technique on the students’ reading comprehension. The t-test result was -6273 and its df was 37, by comparing the significant value. If the probability value is &gt; 0.05, H0 is accepted and Ha is rejected. If the probability value is &lt; 0.05, Ha is accepted and H0 is rejected. Because the p-value was 0.000 &lt; 0.05, thus, Ha is accepted and H0 is rejected.
PEMBERDAYAAN MASYARAKAT DESA TANJUNG BERAKIT, KABUPATEN BINTAN MELALUI PENGEMBANGAN KERAJINAN BATIK

Tanjung Berakit is one of the Bintan regencies which is on the Indonesian border. A common problem experienced by people in the border region is the low level of the community's economy. Therefore, there is a need for community empowerment so that they can provide knowledge and skills to support tourism and the community's economy, one of which is in the field of crafts. The handicrafts that will be developed are batik with creative motifs that reflect the Tanjung Berakit area and Bintan Regency. The empowerment of Tanjung Berakit community is related to the specialties of batik in the region carried out with the socialization and training of making batik. Activities in the Serving Doctoral program consist of socialization, preparation of tools and materials to be used and implementation of activities or practices.
PERSONAL QUALITIES OF FUTURE OFFICERS AND THE ORGANIZATION OF FREE TIME BY THEM

Leisure organization is an integral part of the moral and psychological support for the training and use of the Armed Forces. Psychological features of leisure time of cadets have not been sufficiently studied in the space of senior youth age and in connection with the chosen profession. The purpose of our article was the influence of personal qualities on the organization of leisure of cadets. Empirical methods: role model test by Kelly D. O., 16 RF- personal questionnaire by Kettel R. B. Method of selection of factors: principal component method. Rotation method: varimax with Kaiser normalization. The data obtained were interpreted. Five factors have been identified. The first factor is the most pronounced, it has been called "mind and conscience when using free time". The difference in the semantic constructs of personality depending on the level of organization of free time by cadets is considered.Key words: leisure, cadets, semantic constructs, the age of older youth, the profession of a military man, factor analysis.
Efficiency of Virtualization over MEC plus Cloud

We study average performance and costs for routing service requests in a virtualized environment, where either the MEC or the Cloud can serve user's requests. Employing a simple yet precise analytical model validated via simulation, we focus on latency, service request losses, energy consumption, and provider utility. The model is very effective in providing insight and guidelines for setting up server selection strategies with different characteristics (e.g., energy consumption, penalties, etc.) and performance requirements. In particular, our results show that the MEC is latency-efficient but incurs higher costs than Cloud, and then, to make its use sustainable, it is desirable that the MEC server is powered with renewable source energy.
Understanding Question Pair Similarity

One of the most important areas where the Natural Language Process of Machine Learning may help is determining if two questions are similar. The model we create can instantly detect if a question is similar to one that has already been posed. To find the underlying patterns in our data, we'll do a complete Exploratory Data Analysis. Based on our observations, we will do feature engineering. We'll try out a few different modelling strategies to determine which one works the best and keeps the greatest outcomes.
API-led Connectivity Using Mulesoft For Healthcare

The API-led business model is a new way of thinking about how to engage with partners and customers through APIs. The traditional approaches were designed for business use cases having limited endpoints and speed of delivery is not critical. Traditional approaches include P2P and E2E. To overcome these drawbacks, a new approach of API-led connectivity is used. The primary aim of API-led connectivity is to allow the integration flows to be reused by means of many events and to be reused within the integration platform. This paper focuses on creating an API- led network which is agile, reusable, and fits business requirements. This network will be built for the health care system using Allscripts and Fitbit APIs. To implement API -led networks in this paper MuleSoft platform is used and API is built using the API development cycle. Depending on the business requirements on the search for API and connector already present on Anypoint App exchange. Using available component flow is created to connect EHR system systems and different devices like Fitbit. Both API are protected with OAuth 2.0 which is handled with a separate flow for initiating the communication between the system and source API. After doing the required transformation to data fetch from source API data is pushed to the Salesforce object. Using different services provided by Mulesoft, an API-led network was built in which EHR and the Fitbit device were integrated. As this development process followed agile behavior it helped in meeting business requirements for building networks. The data was successfully fetched, processed, and transferred from the EHR system and the Fitbit device to the Salesforce object.
EFEKTIVITAS METODE DEMONSTRASI DALAM MENINGKATKAN KETERAMPILAN VOKASIONAL MEMBUAT SNACK BOUQUET BAGI ANAK TUNARUNGU KELAS XI SMALB DI SLB PEDULI ANAK BANGSA PAYAKUMBUH

This research discusses the problems found by the author in Payakumbuh Children's Care Special School. This research describes how learning skills that have not had any new innovations or new skills given to children so that children start to get bored with the same skills that are learned such as gardening, sewing, and making tissue boxes from drink bottles. In connection with these problems, the author tries to provide types of vocational skills in different ways, different forms and by generating selling points that can help deaf students themselves after they finish their education, namely by presenting vocational skills to make Snack Bouquet. This research uses experimental research. The method used to determine whether the demonstration model could be effectively used in making snack bouquet skills. The subjects of this study were deaf children in class XI at Payakumbuh Children's Care School, consisting of 3 girls and 2 boys. The result of this research is that there is an increase in the child's ability to make snack bouquets after being given treatment using a demonstration model proven by the Wilcoxon Sign Rank Test the resulting value is 2.041 with probability and Asymp sign. (2-tailed) = 0.041 so that the probability obtained is 0.041 <0.05, thus Ho is rejected and Ha is accepted so that the demonstration method is effective to improve vocational skills in making snack bouquets for  deaf class XI children at SLB Peduli Anak Bangsa Payakumbuh.
How Are Learned Perception-Based Controllers Impacted by the Limits of Robust Control?

The difficulty of optimal control problems has classically been characterized in terms of system properties such as minimum eigenvalues of controllability/observability gramians. We revisit these characterizations in the context of the increasing popularity of data-driven techniques like reinforcement learning (RL), and in control settings where input observations are high-dimensional images and transition dynamics are unknown. Specifically, we ask: to what extent are quantifiable control and perceptual difficulty metrics of a task predictive of the performance and sample complexity of data-driven controllers? We modulate two different types of partial observability in a cartpole stick-balancing problem -- (i) the height of one visible fixation point on the cartpole, which can be used to tune fundamental limits of performance achievable by any controller, and by (ii) the level of perception noise in the fixation point position inferred from depth or RGB images of the cartpole. In these settings, we empirically study two popular families of controllers: RL and system identification-based $H_\infty$ control, using visually estimated system state. Our results show that the fundamental limits of robust control have corresponding implications for the sample-efficiency and performance of learned perception-based controllers. Visit our project website this https URL for more information.
Penerapan Metode Simple Columnar Transposition (SCTR) untuk Aplikasi Enkripsi Teks Berbasis Android

The development of communication technology such as the use of mobile phones based on android. Android has the capability of getting good as personal computer and it has a large storage area. Android users use it to store important data. Critical data that is stored to make various ways to membobolnya. The role of cryptography is indispensable for securing the data. Cryptography is the science to encode a message, while to keep the message or document is secure and cannot be read by those who are not entitled to use encryption. The application of encryption uses a symmetric algorithm. On the application of this method used is Simple Columnar Transposition method. Simple Columnar Transposition method by dividing plainteks into blocks with a key length (k) certain then these blocks are arranged in the form of rows and columns. The making of this application using the JAVA programming language and XML. The application is made for a mobile with Android using the Studio. This application was eventually shown on android mobile phone users. The application used to encode text/sentence, the result of encryption in the form of chipertext, and the result of decrypting plaintext form.
Penerapan Least Squares Support Vector Machines (LSSVM) dalam Peramalan Indonesia Composite Index

In the era of very rapidly advancing technology like today, both internet technology and computerization have made various corporate agencies or investors start thinking about the importance of the stock market in their capital division. Previously there were various purchases by the company's capital, such: gold, land, buildings, production machines, but at this time the purchase of capital shares should also start to attract attention and these purchases are legal investments. Various kinds of company shares that are sold can already be seen through the internet and it is very easy and attractive for companies that will make capital purchases, even the model can be chosen for both long-term and short-term capital purchases. This stock price forecasting system using the Least Squares Support Vector Machines (LSSVM) method will be very popular with investors to help determine conclusions for buying shares because it can reduce losses or even make the right decisions so that it will increase profits for investors or companies. Least Squares Support Vector Machines is a simpler model and has been modified from the previous model, namely: Support Vector Machines (SVM) method. Solving linear equations can be solved in a simpler way using LSSVM compared to using SVM. The variable used in the network is the close price variable. The kernel that used for this study is the RBF kernel. This study consists of three phases or stages. The first stage uses 400 historical data rows, second stage uses 800 historical data rows, and the third stage uses 1200 rows of data. This research obtains the best result of accuracy in the third stage. The third stage has the smallest MSE value: 0.00025248 by using 1200 rows of historical data.
CONTENT-PROCEDURAL FOUNDATIONS OF STEM EDUCATION IN THE USA

The article reveals content-procedural foundations of STEM education in the USA. On the basis of using a number of theoretical research methods (analysis, synthesis, generalization, comparison) the essence of the studied phenomenon was revealed. The types of high schools, that provide educational services in the field of STEM, are characterized, namely: selective schools, which admit gifted students who have outstanding abilities in the field of STEM; inclusive schools that serve students from all backgrounds, targeting lowincome youth, minorities and other traditionally under-represented categories of student youth; STEM-Focused Career and Technical Education (CTE) Schools, which help a wide range of high school students gain insight into the practical application of knowledge in STEM disciplines and prepare for work in the field of STEM.
Theoretical and Methodological Aspects of Music Teacher’s Professional Training in Higher Education Institutions

The article considers the main aspects of professional and pedagogical training of a teacher of music disciplines in higher education institutions and reveals its educational functions in the artistic and pedagogical process. The specifics of the professional activity of a music teacher are outlined, the approaches of scientists to the condition and ways to improve it are presented. The connection between the theoretical and practical training of a music teacher and the real specifics of future pedagogical activity is established. The scientific directions, focused mainly on the specifics of musical activity, providing improvement of preparation of teachers of musical art for work in general education system are investigated. Identified the methodological approaches. Emphasized the importance of musical and pedagogical knowledge of a music teacher, the interdependence of his theoretical training and performance practice. Scientific sources are analyzed, where the methodological aspect in the system of training future art specialists is considered. Revealed the necessity of forming and further improvement of artistic, pedagogical and performing training students as the essence of pedagogical skill of the future teacher of musical disciplines.
Artificial Generation of Realistic Voices

In this paper, we propose an end-to-end text-to-speech system deployment wherein a user feeds input text data which gets synthesized, variated, and altered into artificial voice at the output end. To create a text-to-speech model, that is, a model capable of generating speech with the help of trained datasets. It follows a process which organizes the entire function to present the output sequence in three parts. These three parts are Speaker Encoder, Synthesizer, and Vocoder. Subsequently, using datasets, the model accomplishes generation of voice with prior training and maintains the naturalness of speech throughout. For naturalness of speech we implement a zero-shot adaption technique. The primary capability of the model is to provide the ability of regeneration of voice, which has a variety of applications in the advancement of the domain of speech synthesis. With the help of speaker encoder, our model synthesizes user generated voice if the user wants the output trained on his/her voice which is feeded through the mic, present in GUI. Regeneration capabilities lie within the domain Voice Regeneration which generates similar voice waveforms for any text.
Image super resolution algorithm based on multi-directional features

Super-resolution of single image aims to reconstruct its high-resolution version from a single low-resolution image. The existing reconstruction methods are inadequate in edge preservation and edge artifact suppression. In this paper, we propose a new SR method based on the sparsity along the directions of image gradients and the similarity of directional features. First, the Directionlet transform is used to extract the directional features of the image; then the directional total variation regular terms and the similarity weight calculation of the non-local mean are applied to the extracted directional features, resulting in that the detailed features of the image can be preserved effectively and the edge artifacts can be suppressed better. Finally, we use a framework of templates for first-order conic solvers with an energy function of minimal error to reconstruct the SR image. Experimental results show that our method that the superiority of our proposed method over the state-of-the-art algorithms.
3D Multi-Camera Calibration with a Fractal Encoded Multi-Shape Target

Robust multi-camera calibration is a fundamental task for all multi-view camera systems, leveraging discreet camera model fitting from sparse target observations. Stereo systems, photogrammetry and light-field arrays have all demonstrated the need for geometrically consistent calibrations to achieve higherlevels of sub-pixel localization accuracy for improved depth estimation. This work presents a calibration target that leverages multi-directional features to achieve improved dense calibrations of camera systems. We begin by presenting a 2D target that uses an encoded feature set, each with 12 bits of uniqueness for flexible patterning and easy identification. These features combine orthogonal sets of straight and circular binary edges, along with Gaussian peaks. Our proposed feature extraction algorithm uses steerable filters for edge localization, and an ellipsoidal peak fitting for the circle center estimation. Feature uniqueness is used for associativity across views, which is combined into a 3D pose graph for nonlinear optimization. Existing camera models are leveraged for intrinsic and extrinsic estimates, demonstrating a reduction in mean re-projection error of for stereo calibration from 0.2 pixels to 0.01 pixels when using a traditional checkerboard and the proposed target respectively.
Quantum Certainty Mechanics

Quantum certainty mechanics is a theory for measuring the position and momentum of a particle. Mathematically proven certainty principle from uncertainty principle, which is basically one of the most important formulas of quantum certainty mechanics  theory. The principle of uncertainty can be proved by the principle of certainty and why uncertainty comes can also be proved. The principle of certainty can be proved from the theory of relativity and in the uncertainty principle equation, the principle of certainty can be proved by fulfilling the conditions of the principle of uncertainty by multiplying the uncertain constant with the certain values of momentum-position and energy-time. The principle of certainty  proves  that  the calculation of θ ≥π/2 between the particle and the wave involved in the particle leads to uncertainty. But calculating with θ=0 does not bring uncertainty. Again, if the total energy E of the particle is measured accurately in the laboratory, the momentum and position can be measured with certainty. Quantum certainty mechanics has been established by combining Newtonian Mechanics, Relativity Theory and Quantum Mechanics. Quantum entanglement can be explained by protecting the  conservation law of energy.
PENGARUH MODEL PEMBELAJARAN TEAM GAME TURNAMENT BERBANTUAN MEDIA QUESTION CARD TERHADAP HASIL BELAJAR SISWA PADA MATA PELAJARAN FISIKA KELAS XI SMA N 3 PADANG PANJANG

AbstractThis study aims to determine the influence of application of Team Game Tournament learning model with media assisted Question Card on student learning outcomes in physics class XI MIPA SMA N 3 Padang Panjang. This type of research is quantitative with the Quasy experiment method. Based on the results of data analysis obtained the average value of class experiments using the Learning model Team Game Tournament  assisted media Question Card is 83 with standard deviation (SD) 4, 125 while the average value in the control class 76 , 64, Standard deviation (SD) 3.894. Based on t-Test calculations obtained T_hitung = 6, 247 whereas T_tabel at α 0.05 is 2.000. If compared, then T_hitung greater than T_tabel that is 6.247 > 2.000 thus, Team Game Tournament with the media related Question Card has a significant effect on student learning outcomes in physics class XI MIPA SMA N 3 Padang Panjang.
Traffic Sign Detection and Recognition Using Deep learning based- Convolutional Neural Network Algorithm

The concept of Deep Convolutional Neural Organizations (CNNs) is a quickly arising new zone for Automatic traffic sign detection and recognition among the few master frameworks, such as independent driving and driver assistance. Here, in this paper, for traffic sign detection, we have utilized another methodology that uses a newly developed identification calculation and an RGB-based tone thresholding procedure. Results of the proposed identification and acknowledgement approaches are assessed on German Traffic Sign Detection dataset. Moreover, this work incorporates execution and examination of Deep Learning based designs for the grouping of 43 unique kinds of traffic signs. Also, well known Convolutional Neural Network based structures were assessed with respect to the accuracy of classification and prediction speed. Finally, we have also suggested an effective CNN method that gives high accuracy and precision as well in the light of the results achieved.
LibGuides: Research Data Support Services for Researchers: Sharing and Re-using Data

This guide supports the University’s Policy on Research Data Management contained within the Research Integrity Policy Framework. The guide provides guidance for Swansea University researchers on expectations, obligations, advice and support for research Information on how to go about sharing your research data and re-using other people's data
Smorgasbord of Simple Statistical Tests

The following are a sampling of one-liner tests. They provide a wealth of information on any numeric series/column with little code required. If you are doing upfront data exploration, put a chunk of these at the beginning of your program.