Reviewerly/exHarmony huggingface dataset:
Inductive Approach Used in Teaching Speaking Skill: A Content Analysis

&lt;p&gt;This study aims to determine the feasibility of implementing an inductive approach in teaching speaking skills. The qualitative descriptive was used in this study by using content analysis technique. The technique of obtaining data used documentation. The data were analyzed by coding, display, and verification. The data analysis was carried out in depth by using some theories related to the inductive approach in teaching speaking skills. The results of the study indicate the interrelated of the implementation and responses of the students in using this approach. The results show that the inductive approach is very helpful for students in learning to speak English because it is based on the examples given and they have learnt to find patterns in English speaking. By seeing the examples, they also learn how to imitate the way how people say in English and they are actively involved in the teaching and learning process. Furthermore, it is suggested that inductive approach can be used in speaking class.&lt;/p&gt;&lt;p&gt; &lt;/p&gt;&lt;p&gt; &lt;/p&gt;&lt;p&gt; &lt;/p&gt;
ACTIVATION OF EDUCATIONAL AND COGNITIVE ACTIVITY OF STUDENTS IN THE CONDITIONS OF DISTANCE LEARNING

The article reveals the essence of the concept of intensification of educational and cognitive activities, analyzes the lecture form of learning and test assessment of knowledge as the most common ways to transfer, obtain information and control the acquisition of knowledge in the context of activating educational and cognitive activities of students during traditional (classroom) and remote format. It was found that the basis of cognitive activity is a complex intertwining of intellectual, volitional and emotional spheres of personality. Means of activating cognitive activity stimulate will and attention, expand opportunities for memorization, increase mental performance, optimize the functional state of students. The leading motivating factor for active mental activity of the student, as the main condition for the effectiveness and quality of learning, should be internal motivation related to personal development, professional growth, self-actualization, conscious desire to solve a problem, achieve something in life, not external coercive measures.&#x0D; Activation of educational and cognitive activities of students in the conditions of distance learning is facilitated by the following factors: awareness of the need, importance, expediency of studying the subject as a whole and by sections (topics); problem-solving, independent search and «discovery» of new knowledge; the relationship of new material with previously acquired knowledge: the more new information is related to previously acquired knowledge, the more interesting it is; educational material should be difficult enough, but feasible (too light or too complex material reduces cognitive interest); the more often the student's work is checked and evaluated (including by himself, educational devices, etc.), the more interesting it is for him to work.
Automated Writing Support for Swedish Learners

This paper describes a tool developed for lexical and grammatical analysis of Swedish text and providing automated feedback for language learners. The system looks for words and word sequences that are likely to contain errors and suggests how to correct them using different non-neural models. The feedback consists of alternative word and word sequence suggestions and morphological features which need to be corrected. Although the system is able to provide reasonable feedback which is believed to be useful for language learners, it still needs further improvements to address the drawbacks such as low precision.
PENGEMBANGAN MODUL PPKN MENGGUNAKAN MODEL EXAMPLE NON EXAMPLE UNTUK MENINGKATKAN AKTIVITAS BELAJAR SISWA

This study aims to produce PPKn modules on environmental love by using the example non example learning model to improve student learning activities. The results showed that the feasibility assessment by material experts obtained an average of 91.6%, the feasibility assessment by linguists obtained an average of 92.1%, the feasibility assessment by design experts obtained an average of 80%. Individual trials with an average of 80.5% in the good category, small group trials with an average of 85.4% in the excellent category, and limited field trials with an average of 88.4% in the very good category. The results of observations of student activities observed an average of 92.4%, The results of observations of student activities asked an average of 85.6%, The results of observations of student activities tried with an average of 84.9%, The results of observations of student activities associated with reasoning an average of 89.4%, the results of observations of student activities communicate with an average of 83.9%. So the conclusion is that the PPKn module on environmental love using the example non example learning model is declared effective in generating student learning activities and outcomes. This is evidenced from the student learning achievement test. At the time of the pretest, the average value of the students was 69.8 and after using the module (posttest), that was 82.3
Information Hiding Model Based on Channel Construction of Orthogonal Basis

Secret information communication model based on channel construction of orthogonal basis can implement secret information hiding and recovery without a key. The orthogonal basis is constructed by the media carrier's self-correlation. Carrier and secret information channels are constructed independently. And it has good properties of avoiding detection. The experiments show that the model with proper carrier components and threshold of secret information coding has the capacity of secret information and robustness. And the secret information capacity and anti-noise capability can be improved by compressed and error correcting or checking codes.
Theoretical Fundamentals of Children with Intellectual Disorders’ Extracurricular Education Practice in Ukraine

The article examines the problem of theoretical foundations of people with intellectual disabilities’ out-of-school education, its special significance as a social institution, one of the main factors of socio-cultural, professional mobility of the individual, which are deprived in socio-economic terms in society. It is established that the specifics of the activities of out-of-school education as an element of society, designed to fulfil the state order for the socialization of children and to promote social protection of the individual, its social formation and development. It is established that the effective socio-pedagogical activity of out-of-school educational institutions is due to the content, technological and organizational-pedagogical components that allow for an individualized approach to the child in the process of socialization (given the peculiarities of its habilitation due to the type and severity of intellectual disability); to reveal and develop the adaptive potential of a child with intellectual disabilities in the process of collective creative work in the natural environment of peers; implement mechanisms for coordinated interaction of social partners. It is determined that the leading role in the organization of extracurricular educational institutions for children with intellectual disabilities is assigned to methodological work aimed at developing and updating the extracurricular education content and methods of various areas. The article focuses on the development of individual programs of group work to socialize schoolchildren with intellectual disabilities.
A Healthy Lifestyle And Its Importance

This article provides for a healthy lifestyle among the population and young people, schoolchildren and students of colleges, institutions, improving medical culture and how to protect one's health. Also, conducted on new pedagogical technologies and innovative methods.
Design and Implementation of Missing Data Classification Technique for IoT Applications Using Artificial Intelligence

The combination of various sensors with different data methods is a common technique used to increase precision in the classification of IoT health data. However, for even the assessment outcomes, all modalities are barely available and this scarcity of evidence poses significant barriers to multimodal education. Driven by recent developments in deep education, we are providing a cross-neural network for the segmentation of the IoT Health Data Classification, which is trained on data modalities not all available during trials. In IoT Health Data Classification, we train our architecture with a cost function that is especially tailored to unbalanced classes. We are providing the device with a benchmark data set with incomplete data. Assuming that they are not present in the research process, our methodology goes beyond both the CNN training and the collection of two CNNs trained in the missing modality by utilising time data
A Survey On Telugu Optical Character Recognition From Digital Images

Images play an essential function in the electronic media to share information. Nowadays, each event is going to be recorded in the arrangement of digital images. Text from the image file won't be in a format on the computer. OCR (Optical Character Recognition) for English vocabulary is well constructed. Currently, there's a requirement of OCR for Indian languages to maintain historical documents composed mainly in Indian languages to arrange publications in the library and for program form processing. OCR for the Telugu language is challenging as consonants and vowels plays a vital role in forming words along with vattus and gunithas. It may be a mixture of vowels and consonants that may form a compound character. This paper presents research on methods utilized in the OCR method for the Telugu Language until today.
Approximation of noisy data using multivariate splines and finite element methods

We compare a recently proposed multivariate spline based on mixed partial derivatives with two other standard splines for the scattered data smoothing problem. The splines are defined as the minimiser of a penalised least squares functional. The penalties are based on partial differential operators, and are integrated using the finite element method. We compare three methods to two problems: to remove the mixture of Gaussian and impulsive noise from an image, and to recover a continuous function from a set of noisy observations.
Systematic Literature Review: Current Products, Topic, and Implementation of Graph Database

Planning, developing, and updating software cannot be separated from the role of the database. From various types of databases, graph databases are considered to have various advantages over their predecessor, relational databases. Graph databases then become the latest trend in the software and data science industry, apart from the development of graph theory itself. The proliferation of research on GDB in the last decade raises questions about what topics are associated with GDB, what industries use GDB in its data processing, what the GDB models are, and what types of GDB have been used most frequently by users in the last few years. This article aims to answer these questions through a Literature Review, which is carried out by determining objectives, determining the limits of review coverage, determining inclusion and exclusion criteria for data retrieval, data extraction, and quality assessment. Based on a review of 60 studies, several research topics related to GDB are Semantic Web, Big Data, and Parallel computing. A total of 19 (30%) studies used Neo4j as their database. Apart from Social Networks, the industries that implement GDB the most are the Transportation sector, Scientific Article Networks, and general sectors such as Enterprise Data, Biological data, and History data. This Literature Review concludes that research on the topic of the Graph Database is still developing in the future. This is shown by the breadth of application and the variety of new derivatives of GDB products offered by researchers to address existing problems.
Оrganization of Independent Work of Students in the Context of Innovation Processes

The article deals with the problem of organizing independent work of students. The methodology of using the organizational management model, its essence, and main advantages in the modular training system are revealed. Individualization of the content of the modular system in accordance with the real needs of each student is a consistent program of self-development. An individual project was proposed, which was formed on the basis of establishing the actual level of knowledge, and skills in a certain field of activity or, if necessary, the development of specific personal qualities. The implementation of the managerial principle of obligation depends on the level of formation of such an important quality of the subject of management as «ability to self-manage». Violation of this principle leads to non-fulfillment of an individual plan, and, as a result, the appearens of the sense of dissatisfaction and the decrease in student activity. The student must learn to change the entire hierarchy of forms of their own activity consciously and purposefully: communication, behavior, activities and experiences. Students were assisted in improving their ability to manage themselves, starting at the stage where the student showed the more sustained interest. The introduction of operational models of operational management makes it possible to reflect the objectivity of the assessment of all types of educational activities, which foreses the creation of conditions under which the existing knowledge and skills are identified as accurately as possible.
Analysis of Key Points of Anti-Seepage Technology in Hydraulic Engineering Construction

The water conservancy project is an important infrastructure to ensure people’s living standards, which is reflected in the protection of people’s lives and property by effectively resisting floods. The anti-seepage technology plays a significant role in affecting the construction quality of water conservancy projects. Under the current strong supervision of water conservancy projects, relevant personnel should pay more attention to the application of anti-seepage technology. From the perspective of actual engineering practice, this paper analyzed the importance of anti-seepage technology, sorted out the causes of leakage, and specifically explored the implementation points of anti-seepage technology in water conservancy project construction.
Privacy Preserving Location based Services Through K-Anonymized Vehicular Social Network

Location-based services (LBS) are the services that are used through users’ mobile devices and provide them the information regarding nearby restaurants, hospitals, gas stations, shopping malls, cinema (to name a few). While using LBS, a user needs to provide his/her location coordinates (geo-coordinates) to the LBS server. The revelation of a user’s location may seriously jeopardize his/her privacy. A common solution to this problem is the use of an intermediate anonymizer server that obfuscate the real location of a user among k other users. However, in this scenario, the anonymizer server must be a trusted and therefore, inherits the trust related issue and may also become a single point of failure. Moreover, if anonymizer compromises then the privacy of all the users is compromised. A vehicular adhoc network (VSN) is a subset of a mobile adhoc network (MANET) with some unique characteristics such as rapid speed of nodes (vehicles) that quickly change topologies. A vehicular social network is a combination of VANET and online social network. A VSN is formed by likeminded drivers/passengers or by common location. Like mobile nodes, the vehicles also utilize LBS services. However, an anonymizer cannot be used in this scenario because it needs to be updated with current locations of vehicles and therefore, jeopardizes the privacy of vehicles. A VSN can significantly help in this scenario. This research proposes a distributed k-anonymity based scheme that considers the social ties between the users of VSN and enable vehicles to use LBS in a privacy preserving manner. The proposed scheme uses a trusted authority (TA) such as a government law enforcement agency, that registers vehicles. However, the TA does not know what services are requested by a vehicle. On the other hand, the LBS server does not know which vehicle is requesting the service. In the end, the computational and communication overhead of the scheme is presented. The low computational overhead of TA, LBS server and vehicles shows that LBS can serve several vehicles in a very short time. Similarly, the TA can register and provide pseudo-identities to a number of vehicles without any significant delays.
REVIEW THE DEEP LEARNING TECHNIQUE FOR MISSING DATA CLASSIFICATION IN IOT APPLICATIONS FOR NETWORK PERFORMANCE IMPROVEMENT

In order to ensure product safety and increase production quality, The construction of mine Internet of Things networks continues to accelerate mining enterprises. Given the large increase in the number of networked devices connectivity capability in the mine, there is considerable strain on the mine network communication facilities. We suggest an Innovative Solution Using Deep Learning for Missing Data Classification in IoT Network Performance Enhancement System Market Classifier based on neural networks to improve the quality of service in the connectivity infrastructure of mine networks. The classifier uses a transformation wavelet to delete the data flow and to build compliance characteristics to identify the market categories of the system.Owing to the findings of the classification, the system changes the specifications of the network services given to the terminal equipment in a versatile manner. In this way, the system's network capacity can be fairly distributed. We assess the output of the classifier model using the test data collection. We review the deep learning technique in IoT applications for Network Improvement for missing data classification
Research on Human Resource Management for Telework Informatization under the Background of Epidemic Prevention

The Corona Virus Disease in 2019 will have a serious impact on the normal operation of various industries. Under the environment of resuming work and production and ensuring safety, remote online office has become a core option for the operation of various industries. At present, remote office has met a lot of troubles, such as information asymmetry, inefficiency, regulatory difficulties, communication barriers, weakened confidentiality, and so on. This article focuses on exploring the mechanism of human resource management in remote office informatization in the context of epidemic prevention and control, and proposes distance education innovation for employee training, big data transformation performance evaluation, and cloud computing. This article also focuses on solving the problems existed in the remote office. It suggests some useful and innovative human resource management paths. For example, improving data sharing, network optimization and remote collaborative office and others, all of them offer a good idea which provides human resource decision-making reference for the orderly resumption of work and production in various industries.
Towards a Quantitative Model to Deal with Uncertainty Management in Software Projects

The evolution of thinking in project management has raised interest in areas not yet explored by researchers and practitioners of project management, including the management of uncertainties associated with risk management. The correct risk and uncertainty management in software projects can represent a competitive differential for the software development industry. Despite the increasing use of uncertainty management strategies, many projects still fail. Some recent studies show that the current techniques used to manage uncertainties organize the project's known information, but give little or no indication of the unknown information or uncertainties associated with the project. These techniques do not take into account the impact of existing dependency and interdependence relationships between the various sources of uncertainties in the project. This work will apply Action Research to develop a model with a focus on uncertainty quantification techniques. This work aims to present a model with a focus on uncertainty quantification techniques that take into account the relationships of dependencies and interdependence that exist between the sources of risks and uncertainties in software projects and as a result, contribute with the advance of state of the art in the practice of risk and uncertainty management in project software.
A Study And Analysis Of Forecasts In Resource Allocation Using ARIMA In Cloud Environment

Cloud computing refers to the delivering or usage of hosted services over internet rather than a traditional data center. Hosted services can be renting infrastructure/resources on demand or using the cloud as a platform to develop applications or using the cloud to host software that are accessed by clients. The bottom line is to obtain affordable resources from a provider and pay as you go in a flexible manner. In doing so, not all resources need to be obtained upfront. The initial capacity can be rented out and the remaining can be scaled as per the need. To handle such scalability, auto-scaling systems helps tackling the need to maintain the finite set of resources that can serve the current need and on the other hand also reduce the resources when the current need decreases. Very often in a cloud based environment it makes sense to adapt proactive strategies to scale the resources than to react after the surge had occurred. The proactive strategies use a quantified metric as a input to provision resources on demand that could meet the future expectations. This metric is obtained by carefully analysing the historical data of the application and in turn can influence the scaling decisions. Conclusions are drawn about the accuracy of the metric based on different timelines of historical information along with the confidence levels with which the prediction is done.