Reviewerly/exHarmony huggingface dataset:
Modular Teaching Technology Based on Scientific Activity

the article is based on analyzing the effectiveness of implementing modular training technology in teaching process and in the process of scientific activity. As well as, author analyses the steps of its usage. A module is a separate unit that includes theoretical material, training tasks, and methodological recommendations for students. The constituent element of the module is control questions and tests, as well as keys for self-checking or mutual checking. By studying the module, students achieve a specific didactic or pedagogical goal. The content of the training session is constructed from several logically interconnected modules, each of which solves a specific educational task. The execution of the module is given a fixed time. Together, all modular blocks are aimed at achieving substantive and personal results. The module is an independent structural unit, which in some cases allows individual students to listen to not the entire course, but only a number of modules. This allows you to optimally plan the individual and independent work of gifted students. For the active introduction of modular learning technology, it is necessary to increase student motivation. Pupils should have a well-developed ability of independent cognitive activity. It is important that the material base of the educational institution makes it possible to provide students with individual sets for working in modular lessons.
IMPLEMENTASI MODEL PEMBELAJARAN TEAM GAME TOURNAMENT(TGT) UNTUK MENINGKATKAN AKTIFITAS BELAJAR SISWA

This study aims to: (1) determine the responses of students in learning mathematics with a cooperative model type Team Game Tournament (TGT). (2) determine whether using the cooperative model type Team Game Tournament (TGT) can improve students' mathematics learning activities. The type of research used is Classroom Action Research (CAR). The sample in this study were all grade V students of SD Negeri 1 Plumbon in the academic year 2019/2020 as many as 24 students. The instruments used in this study were observation, documentation and questionnaires.&#x0D; Based on the results of the study, it was concluded that: (1) The fifth grade students of SD Negeri 1 Plumbon gave a positive response to the implementation of learning mathematics using the Team Game Tournament (TGT) cooperative model. (2) the use of the Team Game Tournament (TGT) type cooperative model can increase student learning activities in the fifth grade mathematics subject of SD Negeri 1 Plumbon. This increase can be seen in the results of the observation sheet and questionnaire. Based on the observation sheet, it was found that the average percentage increase in pre-cycle was 36.97% to 61.45% in cycle I and 72.39% in cycle II. Meanwhile, based on the student learning activity questionnaire using the cooperative type Team Game Tournament (TGT) model, it also increased from the pre-cycle by 61.97%, increased to 74.88% in cycle I and increased again in cycle II which was 80.20%.
Linguistic Diversity in Online Space - A Study on South Asian Languages

Rich linguistic diversity is hallmark of South Asian regions that comprises eight nations. Some of the languages are spoken in more than one country, and scripts of few languages are common. This shared commonality increases the cultural diversity within this region. Equally South Asian region is witnessing massive growth of Internet users barring few nations. With the affordable Internet connectivity through multiple telecommunication players, many Internet usersare active in social media.These scenarios are highly congenial for any language to adapt into online platform easily. With this assumption, this article is attempting to explore the linguistic diversity and web presence of SouthAsian languages in online space.To measure the web presence of these languages, this article relies on three sets of data -Wikipedia articles, Google search techniques, and online algorithm.With these three indicators, an attempt would be made to measure the nature and present scenario of adaptability nature of South Asian languages in online space.
Object based Image Retrieval with Segmentation and Extraction of Features using various Methods

This paper proposes Object Based Image Retrieval (OBIR) System with segmenting the objects from the images and then extracting various features from the objects. The objects are the most prominent part of an image which relates more to the human perception. First, the object present in the images is segmented by four different segmentation techniques such as K-means, Active Contours, Edge-Convex hull and Global Thresholding. Later, the color features such as Color Histogram (CH) and Color Coherence Vector (CCV), Texture feature using Local Binary Patterns (LBP) and shape feature using Histogram of Gradients (HOG) are extracted. Finally, with the usage of different segmentation and techniques mentioned above feature are extracted from objects. Results obtained are tabulated and performance study is made.
Decoupling DNS from Congestion Control in Rasterization

Numerous cyberinformaticians would concur that, had it not been for passageways, the simu-lation of outrageous programming may never have happened. Given the present status of "fluffy" correspondence, frameworks builds daringly want the development of flip-flop entryways, which typifies the noteworthy princi-ples of e-casting a ballot innovation. In this work, we focus our efforts on demonstrating that IPv7 and eradication coding are generally incongruent.. [1],[ 3],[5]
Classification of Student Majors with C4.5 and Naive Bayes Algorithms (Case Study: SMAN 2 Bekasi City)

School majors conducted in high school are based on interests and these have a goal to provide opportunities for learners to develop the competence of attitudes, skills competence of learners in accordance with interests, talents, and academic ability in a group of scientific subjects.In this research, the researcher uses two algorithm models that is a comparison between the C4.5 algorithm and also the Naive Bayes algorithm. In this study, the data used is the results of school entrance test data and also the data from psychological results for students who have been declared passed the entrance test school SMAN 2 Bekasi City academic year 2018/2019. By comparison of two data mining classification algorithm, can be proved with accuracy result and AUC value from each algorithm that is for Naive Bayes accuracy = 76,43% and AUC value = 0,846, while for algorithm C4.5 accuracy = 70,29% and AUC value = 0.738.
Multi Scale Hashing Access in Multi-Dimensional Datasets using Bootstrapping

The query is the most widely used in many applications. Computation of multi-dimensional dataset is more complication by using existing algorithms. Showing the spatial results by using the multi-dimensional dataset is implemented in this paper. The existing system ProMiSH (Projection and Multi Scale Hashing) is not performed based on the keyword query searching. The proposed system Ensemble approach with bootstrapping algorithm shows better results. The implementation is done with a spatial dataset with a location-based query keyword search done in the proposed system
Excellent overview of multivariate BC methods

This is a timely paper providing an overview about the plethora of newly emerging multivariate bias correction approaches that have been developed over the recent years.The authors provide recommendation about which approach should be used under which conditions.The paper has the potential to become a key reference for multivariate bias correction approaches.It has an easy to follow clear structure, is well written and falls into the scope of ESD.I have a few minor recommendations which should help to improve its accessibility and impact.
Introduction to the Minitrack on Mixed, Augmented, and Virtual Reality: Co-designed Services and Applications

During the past five years, virtual reality, augmented reality, mixed reality and related technologies have gained a lot of media attention, and availability and usability of the technology is improving.Using
Recent Trends in Wheelchair to Assist the Physically Challenged

In this paper a survey of autonomous wheelchair has been proposed for physically handicapped people, which serves their crucial role for maneuvering by simply moving their neck. To fulfill this objective, this paper involves Arduino board programmed for processing &amp; controlling the wheelchair. Micro switches are used here to sense the neck movements from the disabled person and which further send this to Arduino for taking necessary action to move the wheelchair accordingly. GPS module is integrated with the Arduino to locate the physically disabled person in case of emergencies. In addition to this, GSM module is been used for sending crucial information regarding the physically disabled person’s health issues if any, like body temperature, to further send this to his/her contact person/assigned care-taker. In some special case of physically challenged person who is not able to move any of his/her body part except fingers, this paper gives the better perspective to make a movement of the wheelchair by simply controlling it by virtue of an android app installed on the wheelchair. An android app is developed to serve as inputs for processing and controlling the DC motors for the desired maneuverings.
Generative Modelling and Machine Learning Methods for Travel Behaviour Analysis

The dissertation outlines novel analytical and experimental methods for discrete choice modelling using generative modelling and information theory. It explores the influence of information heterogeneity on large scale datasets using generative modelling. The behaviorally subjective psychometric indicators are replaced with a learning process in an artificial neural network architecture. Part of the dissertation establishes new tools and techniques to model aspects of travel demand and behavioural analysis for the emerging transport and mobility markets. Specically, we consider: (i) What are the strengths, weaknesses and role of generative learning algorithms for behaviour analysis in travel demand modelling? (ii) How to monitor and analyze the identiability and validity of the generative model using Bayesian inference methods? (iii) How to ensure that the methodology is behaviourally consistent? (iv) What is the relationship between the generative learning process and realistic representation of decision making as well as its usefulness in choice modelling? and (v) What are the limitations and assumptions that have needed to develop the generative model systems? This thesis is based on four articles introduced in Chapters 3 to 6. Chapters 3 and 4 introduces a restricted Boltzmann machine learning algorithm for travel behaviour that includes an analysis of modelling discrete choice with and without psychometric indicators. Chapter 5 provides an analysis of information heterogeneity from the perspective of a generative model and how it can extract population taste variation using a Bayesian inference based learning process. One of the most promising applications for generative modelling is for modelling the multiple discretecontinuous data. In Chapter 6, a generative modelling framework is developed to show the process and methodology of capturing higher-order correlation in the data and deriving a process of sampling that can account for the interdependencies between multiple outputs and inputs. A brief background on machine learning principles for discrete choice modelling and newly developed mathematical models and equations related to generative modelling for travel behaviour analysis are provided in the appendices.
Word N-Gram Based Advice for Word Sense Disambiguation in Telugu Natural Language Processing

The word ‘Web-based learning’ sounds good but smells bad when it comes to share the study material online in context of copyright laws. The current problem is that teachers are under the impression that everything they want to share with their students online finds protection under the Doctrine of Fair use under Copyrights law but the unfortunate part is he is totally unaware about the fact that sharing the study material online may not qualify as fair use if the same is shared with students enrolled in an online course outside the campus. The need of the present paper is to make Universities and teachers working there aware about the use of Web based learning without violating the copyright laws of the land. The paper is purely conceptual and only available literatures have been taken in updating the paper following the doctrinal method of study
Extended Kalman filter approach to electric arc furnace forecasting

In this thesis, we propose and implement a new approach for building an online self-adjusting model for prediction of v-i characteristic of a multivariate time series obtained from an operational electrical arc furnace. The proposed methodology is based on the Kalman filtering method, and is used for prediction of the arc furnace voltage using the past history of the current and voltage. The main advantage of the proposed approach over similar earlier related work is the ability to adapt during the operation of the furnace. In this study, three different hybrid models have been developed based on the extended Kalman filtering technique and one of the following methodologies: (i) a linar auto regressive model; (ii) fuzzy logic, (iii) wavelet analysis. The results compare well with those of earlier work and clearly indicate that the augmentation of the above mentioned approaches with the extended Kalman filter improves the prediction accuracy.
A Framework for Multi-document Extractive Summarization of Reviews with Aspect-based Sentiment Analysis

We propose an integrated framework, named Multi-Document Aspect-based Sentiment Extractive Summarization (MD-ASES for short), to automatically generate extractive review summaries based on aspects of a large database with reviews of items such as films, businesses, and companies. Such summaries are got by extracting a subset of sentences as they are in the reviews, based on some relevance criteria. In MD-ASES, initially sentences are grouped in terms of aspects identified as predominant in the reviews. Then, sentences are selected by the similarity of the sentiment expressed about a particular aspect to the overall sentiment of the dataset reviews. Our results show that MD-ASES can successfully preserve the average sentiment of the reviews while including the most important aspects in the summary.
Identifying and Prioritizing the Factors Affecting on the Implementation of Knowledge Management System (Case Study: Yazd Educational Hospitals)

Introduction: At present, in the age of knowledge and knowledge-based, knowledge management has become particularly important. Research shows the effect of knowledge management in achieving a sustainable strategy and competitive advantage. The purpose of this study is to identify and prioritize the factors affecting the implementation of knowledge management system in educational hospitals in Yazd.&#x0D; Methods: In order to conduct this research, first, using effective research background, effective factors were identified. In order to evaluate and compare the factors in relation to each other, a questionnaire was designed as a pairwise comparison and distributed among experts. In order to investigate the relationship between dimensions, the opinions of 20 experts were used. All of these people have more than 10 years of experience in this field. Then, in order to evaluate and identify the indicators, two techniques of AHP and fuzzy dimatel were used to rank the factors.&#x0D; Results: According to the research findings, the highest weight is related to the organizational structure factor and the lowest weight is related to the information technology factor. Identification of the structure factor in the fuzzy dimatel technique as the most effective factor in the study with the results obtained from the fuzzy AHP alignment shows this result in the research.&#x0D; Conclusion: Due to the fact that the organizational structure factor is in the highest importance compared to other factors, the need for more attention of hospital managers to this part of the knowledge management structure shows more than before.
Both Thermochemical and Bacterial Sulfate Reduction Involved in the Formation of MVT Pb-Zn Deposits: A Case Study of the Chipu Pb-Zn Deposit, South China

Revealing the formation mechanisms of reduced sulfur is critical to understanding the genesis of MVT Pb-Zn deposits.A large number of studies have shown that either thermochemical sulfate reduction (TSR) or bacterial sulfate reduction (BSR) play an important role in the formation of MVT Pb-Zn deposits.However, the case of both TSR and BSR involved in the formation of MVT Pb-Zn deposits is rare.Located in the western Yangtze Block, South China, the Upper Yangtze Pb-Zn metallogenic province covers an area of 170,000 km 2 and contains >400 Neoproterozoic-middle Permian carbonate-hosted epigenetic Pb-Zn deposits totaling >26 Mt of Pb + Zn metal reserves.Among these Pb-Zn deposits, the Chipu Pb-Zn deposit is hosted by dolostone of the late Ediacaran Dengying Formation.In the Chipu deposit, metal minerals are mostly composed of sphalerite, galena and pyrite, and gangue minerals comprise mainly calcite, dolomite and quartz accompanied with large amounts of bitumen.NanoSIMS in-situ S isotope analysis shows that δ 34 S values of sulfides (sphalerite and its symbiotic pyrite) range from -31‰ to +34‰, which are significantly different from the previously reported δ 34 S values (+3-+22‰).Furthermore, our sulfur isotope data can be divided into two distinct groups: i) -31‰ to -17‰, and ii) +12‰ to +34‰.The latter group (δ 34 S=+12-+34‰) is overlap with the previously reported sulfur isotope data (δ 34 S=+3-+22‰), implying that TSR plays an important role in the formation of reduced sulfur.However, the former group (δ 34 S =-31 to -17‰) suggests that in addition to TSR, BSR may also play an important role in the formation of S 2-.Further research shows the mixing of two isotopically distinct S 2-that was produced by TSR and BSR caused the formation of the Chipu deposit, which means that the local sulfate reduction occurred during the Pb-Zn mineralization.This provides new insights for understanding the origin and ore exploration of MVT Pb-Zn deposits worldwide.
Experimental Textual-learning Activities for an L2 Italian Initial-literacy Classroom

The paper describes some specific textual learning activities developed for an L2 Italian initial literacy classroom and, in particular, for illiterate multilinguals (mostly unaccompanied foreign minors).The activities belong to an experimental proposal.It consists of a specific textual teaching module integrated with a secondlanguage initial literacy course.The aim was to get the learner immediately accustomed to some types of text, that have been chosen to be suitable for his profile and his needs, as well as perfectly integrated with the contexts and vocabulary proposed in the classroom.Because of the minimum level, the texts were mostly discontinuous.Based on the importance of learners' multilingualism, oral ability, and everyday needs, the specific textual activities proposed in the initial literacy classroom have produced significant results, also with important effects on learners' motivation.
Formula in Tuja'i Molo'opu Custom Speech Procession of Leaders Acceptance in Gorontalo Community

One of the oral literature which is still used in Gorontalo custom event is Tuja'i Molo'opu. Oral literature is uttered at the ceremonial officials' reception in Gorontalo. As other traditions are changing, Tuja'i Molo'opu also along with the changes of the society. Therefore, it needs to be held as the foundation for the preservation of the study of oral literature of Tuja'i Molo'opu. Thus, the Tuja'i Molo'opu ceremony does not complement the Molo'opu ceremony but contains moral messages, which as ancestors, messages to the man who will lead in Gorontalo. The theory used in this research is the theory of orality Albert Bates Lord and Ruth Finnegan. To apply this theory used two approaches, namely, structural and Ethnographic approaches. The structural approach is used to examine the formula composition of the tuja'I Molo'opu text as oral poetry. While the ethnographic approach is used to explore data on leadership the cultural aspects in the Gorontalo community. The results of this research show that formula tuja'i Molo'opu has the formula (1) repetition of a sentence, (2) repetition of the word group/phrase, (3) formula of word repetition, (4) formula of suffix, (5) formula of varied repetition, (6) parallelism.
Inverse biometrics for keystroke dynamics

Tremendous research has been done in the area of computer security using biometrics. But not much has been done in the field of inverse biometrics, which consists of synthesizing artificial biometric samples that can be used for testing exiting biometric systems or protecting them against forgeries. Due to the complexity of the data collection process and privacy and legal issues that are involved, finding volunteers for data collection is a challenging task. In this thesis, we introduce for the first time an inverse biometrics model for keystroke dynamics that can be used to generate as much data as desired. We show that these synthetic data behave as close as possible like real human data, making our inverse biometrics model a model of choice for testing the existing and upcoming biometric systems. Keystrokes dynamics biometric is a behavioural biometric technology, which allows user recognition based on the actions received from the keyboard while interacting with a graphical user interface. The proposed inverse biometric model first learns from the real human data and based on this experience, it generates synthetic users. Each synthetic user generated by model has a unique behaviour, but follows the properties of real human users. A twofold cross-validation testing technique is employed to validate the synthetic data using a suitable model. Comparable performance results are obtained when applying the model to real human data.
Algorithmic Power Ballads

Algorithmic Power Ballads is a performance for Saxophone and autonomous improvisor, with an optional third performer who can use the web interface to handwrite note sequences, and adjust synthesis parameters.The performance system explores shifting power dynamics between acoustic, algorithmic and autonomous performers through modifying the amount of control and agency they have over the sound over the duration of the performance.A higher-level algorithm how strongly the machine listening algorithms, which analyse the saxophone input, influence the rhythmic and melodic patterns generated by the system.The autonomous improvisor is trained on power ballad melodies prior to the performance and in lieu of influence from the saxophonist and live coder strays towards melodic phrases from this musical style.The piece is written in javascript and WebAudio API and uses MMLL a browserbased machine listening library.