Reviewerly/exHarmony huggingface dataset:
The Effectiveness of Using Community Language Learning Method Toward Students Speaking Ability

The purpose of this study was to determine whether the Community Language Learning Method (CLLM) is more effective on the ability to speak 11th-grade students of MIPA SMA Negeri 4, Tanjungpinang. This type of research used in this study is Quasi Research. The tool used to obtain research data is an oral test. The population in this study was eleventh grade students of SMA Negeri 4 Tanjungpinang. This study uses a method that requires students to carry out speaking activities in a group with topics that have been mutually agreed upon in each group. Researcher gave a pretest before learning activities. After the learning activities, the researcher gives a posttest that is added to the rubric of assessment, calculating the average value, and analyzing with the help of a computer application namely SPSS. The application of the Community Language Learning Method (CLLM) during the learning process turns out to have an effect on the ability of students to carry out conversations in groups that have been formed. It can be seen during the teaching and learning process students look more active and enthusiastic about learning to speak situations using the Community Language Learning Method (CLLM).&#x0D;
Solar Potential Estimation and Management Using IoT, Big Data, and Remote Sensing in a Cloud Computing Environment

The problem of finding accurate solar potential and management of the solar plant is the focus of this chapter. It aims to target these issues with the help of the Internet of Things (IoT), big data, remote sensing, and geographic information system (GIS) in a cloud computing environment. The IoT has been used to obtain the daily global horizontal irradiance (GHI) from the pyranometer sensor using USB Wi-Fi adapter. The GHIs calculated from pyranometer and satellite-derived models, such as Copernicus Atmosphere Monitoring Service (CAMS) McClear, Simple Model of the Atmospheric Radiative Transfer of Sunshine (SMARTS), and National Aeronautics and Space Administration (NASA) Prediction of Worldwide Energy Resources (POWER), have been obtained to carry out solar potential assessment. Solar irradiance has been converted from horizontal to tilted surface to obtain optimum tilt angle using Perl Script in a cloud computing environment to get maximum quantum of the irradiance. Semiautomatic feature extraction using k-means clustering algorithm, remote sensing, and GIS has been applied to estimate the usable area at the rooftops of the buildings of the institute located in Northern India. Solar plant management practices have been devised using meteorological data, local weather, and environment conditions. NASA POWER model has given best results in terms of ground-based validation with pyranomoter and tilted GHI approach. This has been evaluated using RMSE value.
Speed Estimation of Moving Vehicle based on Input Images from a Smartphone Camera

Using a mobile smartphone camera, this work explored an alternative approach for estimating the speed of moving vehicles. A hardware prototype is developed to monitor the linear movement of vehicle, then the position of the vehicle is detected by using background subtraction as well as tracked using Gaussian Mixture Models (GMM). By comparing the pixel velocity and the measured speed of vehicle, the average pixel velocity for specific speed is determined. The initial findings show promising results to utilise smartphone technology for traffic monitoring application.
Profil alumni FMIPA dan FKIP Universitas Sriwijaya ditinjau dari variabel dan persepsi pada pekerjaan

One of the aims of the tracer study is to obtain information about the early careers of alumni, so that some of the questions on the questionnaire need to be explored further. The question items discussed were length of study, length of time to get the first job, field of work, total income, alumni's perception of the closeness of the field of study to work, and the suitability of education level on the job, and taking into account gender and average level of competence. The purpose of this study was to analyze the relationship between these variables in the 2020 tracer study data from alumni of 4 science fields at FMIPA and FKIP Unsri. The method used is descriptive statistics and simple correspondence analysis. Almost all respondents from both faculties stated that the suitability of the level of education with the field of work was at the same level. In respondents from both faculties, there is a significant relationship between respondents' perceptions of the closeness of their field of study with their field of work. The average total income of FMIPA respondents is higher than that of FKIP respondents. FMIPA respondents who stated that their field of study was close to their field of work had a high total income and their field of work was self-employed. FKIP respondents who had a length of time to get their first job of less than 3 months (even before graduating) tended to have a length of study of 4 years and their field of work was in government/BUMN and private institutions. The respondents have the perception that their field of study are very close to their field of work. Keywords : tracer study, field of work, first job, Unsri alumni, correspondence analysis
Editorial on Studies of Physical Mathematics

The subject of physical mathematics is concerned with physically motivated mathematics and is different from mathematical physics. The foundations of physical mathematics can be followed back to the earliest reference point of man's endeavors to get nature. For sure, science and physical science were essential for what was called regular way of thinking. Fast development of the Physical sciences, supported by innovative advancement and expanding deliberation in numerical exploration, caused a detachment of technical studies and arithmetic in the twentieth century
Peningkatan Prestasi Belajar Siswa dengan Model Pembelajaran Kooperatif Make A Match pada Mata Pelajaran IPS di Kelas IV SD Inpres Borong Jambu I Kecamatan Manggala Kota Makassar

This study aims to increase student achievement with the Make A Match Cooperative Learning Model in Social Studies Subjects in Class IV SD Inpres Borong Jambu I, Manggala District, Makassar City. This type of research is classroom action research. The subjects of this study were students IV of SD Inpres Borong Jambu I, totaling 20 students, consisting of 11 male students and 9 female students. This research was conducted in two cycles of action. Each cycle contains planning, implementation, observation and reflection activities. The research instrument used is observation, test and documentation. Based on the results of the study showed that student learning outcomes experienced a significant increase in each cycle which was marked enough, the first cycle with an average value of 65.6 then increased in the second cycle with an average value of 77.3 to achieve good criteria. Based on the results obtained, it was concluded that there was a significant increase in social studies learning outcomes for fourth grade students of SD Inpres Borong Jambu I, Manggala District, Makassar City through the Make A Match Cooperative learning model.
Dados e arquivos: desafios para uma profissão abalada pela transformação digital

The article presents the confluence of data and archives in the face of the digital transformation and investigates the main changes, considering reality, emerging problems and new risks and opportunities. Theresearch is descriptive and analytical based on scientific literature. It analyses the impact on the archivist’s object of work and the interrelationships in data, information and document management systems. The reuse of solid information and datacentric trends prevails, motivated by the potential of the technologies.Keywords: data, records management, digital transformation, digital archival science.
A novel ontology framework supporting model-based tourism recommender

&lt;span lang="EN-US"&gt;In this paper, we present a tourism recommender framework based on the cooperation of ontological knowledge base and supervised learning models. Specifically, a new tourism ontology, which not only captures domain knowledge but also specifies knowledge entities in numerical vector space, is presented. The recommendation making process enables machine learning models to work directly with the ontological knowledge base from training step to deployment step. This knowledge base can work well with classification models (e.g., k-nearest neighbours, support vector machines, or naıve bayes). A prototype of the framework is developed and experimental results confirm the feasibility of the proposed framework.&lt;/span&gt;
Distribution of entanglement with variable range interactions

Distribution of quantum entanglement is investigated for an anisotropic quantum XY model with variable range interactions and in the presence of a uniform transverse magnetic field. We report the possibility of \emph{qualitative} growth in the entanglement between distant sites with an increase in the range of interactions that vary either exponentially or polynomially as the distance between the sites increases. Interestingly, we find that such entanglement enhancement is not ubiquitous and is dependent on the factorization points, a specific set of system parameters where the zero-temperature state of the system is fully separable. In particular, we observe that at zero-temperature, when the system parameters are chosen beyond the pair of factorization points, the increments in entanglement length due to variable range interactions are more pronounced compared to the situation when the parameters lie in between the factorization points. By employing the sum of all the bipartite entanglements with respect to a single site, we also show that the shareability of the bipartite entanglements are constrained, thereby establishing their monogamous nature. Furthermore, we note that the factorization points get reallocated depending on the laws of interaction fall-offs and provide an ansatz for the same. We reveal that the temperature at which the canonical equilibrium state becomes entangled from an unentangled one increases with the increase in the range of interactions, thereby demonstrating enhanced robustness in entanglement against temperature in the presence of long-range interactions and only when the system parameters are chosen between the pair of factorization points. We apply an energy-based entanglement witness to provide a justification to the observed robustness with temperature.
A Study on the Development of Product Planning Prediction Model Using Logistic Regression Algorithm

This study was conducted to propose a product planning prediction model using logistic regression algorithm to predict seasonal factors and rapidly changing product trends. First, we collected unstructured data of consumers in portal sites and online markets using web crawling, and analyzed meaningful information about products through preprocessing for transformation of standardized data. The datasets of 11,200 were analyzed by Logistic Regression to analyze consumer satisfaction, frequency analysis, and advantages and disadvantages of products. The result of analysis showed that the satisfaction of consumers was 92% and the defective issues of products were confirmed through frequency analysis. The results of analysis on the use satisfaction, system efficiency, and system effectiveness items of the developed product planning prediction program showed that the satisfaction was high. Defective issues are very meaningful data in that they provide information necessary for quickly recognizing the current problem of products and establishing improvement strategies.
ENHANCED LDA BASED INPUT SELECTION TOWARDS THE SENTIMENTAL ANALYSIS

Big data creates considerable challenges for businesses due to its complexity. The fundamental challenge that firms face is processing and storing large amounts of data. In addition, strategies for dealing with a befuddling amount of raw data in various forms must be enhanced. It is also vital to develop scalable data storage in order to efficiently acquire and retrieve critical information. The importance of feature selection in today's society cannot be overstated. Feature selection is one of the most important factors that can affect classification accuracy. If the dataset has a large number of characteristics, the space will be huge and congested, reducing the classification accuracy rate. It is possible to employ a method that is both efficient and reliable for removing noisy, irrelevant, and redundant data. Then it's just a matter of determining what sentimental analysis entails. Single words from a text document can be utilized as features, or more complex pairings can be retrieved using a variety of approaches that add more information to the feature-document matrix representation. The huge number of properties and relationships that diverse feature types hold, however, causes the high dimensionality problem. As a result, feature selection helps to build effective and efficient sentiment analysis applications by selecting relevant and informative features to enhance classifier performance while reducing processing load. In this work, Enhanced LDA-based feature selection has been applied. LDA is one of the generative statistical models. In basic, the Latent semantic analysis has been the most widely used distributive model with the singular value decomposition. LDA is utilized for removing points from text that empower effective preparing, particularly for huge information analysis.
Subject & Course Guides: DIY LibGuide: DIY: Library Research

A LibGuide showcasing How-To videos and information on accessing library resources and services.
LSC-North Harris Library Research Guides: Drama: E-Books

This is a guide to help students find quality sources when researching plays, theater, and drama.
Sound Design as Viewed by Sound Designers

This chapter proposes knowledge acquisition on the discipline of sound design by questioning its practitioners and therefore exploring its multidisciplinary aspects according to sound designers’ profiles and practices. After presenting the theoretical framework within which this research is conducted, it provides details about the methodological tools implemented in order to investigate this matter (database/cartography and online questionnaire), and then presents a selection of significant findings that bring to light the profile of this emerging profession: Who is a sound designer? How do they learn sound design? How do they design sound? The chapter ends with a discussion of the methods used in this research and the avenues to further explore.
A new dimension of risks in sports: the cyber domain

The digital era and the increasing technological reliance of sport are showing a new face of threat and present a new challenge to the sports organizations – assuring the cybersecurity of the organization, the event, the team. While cybersecurity is a central topic during the design and implementation of the security of major sports events for more than a decade, the sports organizations get newly introduced in the domain, and unfortunately, some happen to learn lessons painfully – by suffering a cyber-attack. The present article aims to examine different kinds of cyber threats to which sports organizations are exposed by studying the most common types of attackers, motivation, and the means used for an attack. The applied methodology includes a literature review and case study performed on cases from three types of categories: major sports events; sports administering bodies, clubs, and athletes. The results of the analysis provide systematic information about the most common attackers’ types, motivations, and approaches which can be used as a foundation for further development of cybersecurity risk assessment of sports organizations.
Strategic Coordination and Navigation of Multiple Wheeled Robots

Pradhan, Buddhadeb Hui, Nirmal Baran Roy, Diptendu SinhaMulti-robot navigation and coordination are addressed in this paper. All the robots are subjected to their own kinematic and dynamic constraints. Genetic algorithm tuned fuzzy logic-based motion planner is compared with the potential field-based motion planner. To avoid the conflicts during the navigation, two different coordination schemes, namely strategic and heuristic, are implemented. Results are compared through computer simulation. Simulation experiments were started with eight number of robots initially, and the number of robots has been increased up to 17 later on due to the need of coordination scheme for the maximum number of robots. Strategic coordination scheme along with the genetic fuzzy-based motion planner is found to perform better than the other combinations concerning the quality of solutions and time taken to reach the goal positions. Computational complexity of different methods has also been compared and presented.
Romantic Influence and Nature Reconsidered: Ralph Waldo Emerson and Henry David Thoreau

This chapter reads the thought and writing of Emerson and Thoreau as exhibiting a knowing self-consciousness about their treatment of self and nature and its use of allusion to the literary and cultural tradition of British Romanticism. What is offered is a fresh awareness of the intellectual and imaginative engagement of the thought of Emerson and Thoreau with the works of Byron, Shelley and Keats. The chapter also points up the affinities rather than the divisions between these two important American writers and their ideas about self and nature.
Tamil Character Recognition, Translation and Transliteration System

Optical Character Recognition (OCR) is the machine conversion of handwritten or typed data into machine encoded scripts. English, is the informal link to all the regional languages in India and is used to publish reports, papers, magazines and records. Monolingual systems are incapable of doing so, thus increasing the need of bilingual frameworks. We have created a character recognition system that converts the user’s input in the Tamil language to English. Additionally, we can also perform transliteration of Tamil to English and vice versa. The bilingual OCR system, “MOZHI VALLAAN,” which has an accuracy of 94%, will be used.
A Comparison of BAT and Firefly Algorithm in Neighborhood based Collaborative Filtering

The recommender system is a knowledge-based filtering system that predicts the users' rating and preference for what they might desire.Simultaneously, the neighborhood method is a promising approach to perform predictions, resulting in a high accuracy based on the common items.This method, furthermore, could affect the resulting accuracy value because when each user provides limited data and sparsity, the accuracy of value might be narrow down as a consequence.In this research, we use the Swarm Intelligent (SI) technique in the recommender system to overcome this problem, whereby SI will train each feature to optimal weight.This technique's main objective is to form better groups of similar users and improve recommendations' accuracy.The intelligent swarm technique used to compare its accuracy to help provide recommendations is the Firefly and Bat Algorithm.The results show that the Firefly Algorithm has slightly better performance than the Bat Algorithm, with a difference in the mean absolute error of 0.02013333.The significance test using the independent t-test method states that no statistically significant difference between Bat and Firefly algorithm.
Impact of Innovations on the Dynamic of Human Capital

The effective implementation of the potential of human capital requires a careful calculation of its quantitative characteristics. First of all, this concerns the determination of the required value of human capital and its changes under the influence of various factors. It is also important to determine the degree of balance of the values of human capital with other types of physical and financial capital. Indicators of the current and strategic balance of human capital and other types of capital provide great opportunities for managing the sustainable and successful development of a firm.
Establishment of UAV Path Planning Model Based on Ant Colony and Simulated Annealing Algorithm

This paper is about the optimal allocation, optimal path planning and optmization of two kinds of UAV (SSA UAV and Radio Relay UAV). Describes the planning and allocation of unmanned aerial vehicles (UAVs) for wildfire rescue and reconnaissance operations in Australia. First of all, we build model using analytic hierarchy process (AHP) and simulated annealing algorithm to determine the constraint conditions, considering safety, capacity, economy, Victoria region of the terrain and the size of the fire, frequency and other factors, through the branch and bound method of integer to get optimal allocation of unmanned aerial vehicle (UAV) is out of the optimal route. Secondly, we use ant colony algorithm to optimize the three-dimensional path of the UAV and plan it. Finally, we use MATLAB to consistency check, to get a comparison matrix, and then the weights for each survey and plan the best path, so as to determine the optimal number of drones and combination, and analyzes the error of the model, to ensure the accuracy of the models.
LibGuides: Systematic reviews: Steps

Overview of systematic review steps and resources to assist researchers conducting reviews.
Selection-Expansion: A Unifying Framework for Motion-Planning and Diversity Search Algorithms

Reinforcement learning agents need a reward signal to learn successful policies. When this signal is sparse or the corresponding gradient is deceptive, such agents need a dedicated mechanism to efficiently explore their search space without relying on the reward. Looking for a large diversity of behaviors or using Motion Planning (MP) algorithms are two options in this context. In this paper, we build on the common roots between these two options to investigate the properties of two diversity search algorithms, the Novelty Search and the Goal Exploration Process algorithms. These algorithms look for diversity in an outcome space or behavioral space which is generally hand-designed to represent what matters for a given task. The relation to MP algorithms reveals that the smoothness, or lack of smoothness of the mapping between the policy parameter space and the outcome space plays a key role in the search efficiency. In particular, we show empirically that, if the mapping is smooth enough, i.e. if two close policies in the parameter space lead to similar outcomes, then diversity algorithms tend to inherit exploration properties of MP algorithms. By contrast, if it is not, diversity algorithms lose the properties of their MP counterparts and their performance strongly depends on heuristics like filtering mechanisms.