Reviewerly/exHarmony huggingface dataset:
Bilingual Matching Algorithm for Data De-Duplication in E-Governance Large Scale Heterogeneous Datasets

The rapid growth and advancements in the field of Information Technology, Cloud Computing and Internet of Things (IoT), paved the way for unprecedented increase in the data that they have produced. The huge data generated from different sources have distinct characteristics in terms of its size, forms and the speed at which the data is generated. This situation has led to the difficulty in processing these datasets by using the traditional tools and techniques. In this paper, a bilingual matching algorithm is proposed to identify and eliminate duplicate data from the large scale datasets collected across various public sector administrative departments such as Public Distribution System (PDS), Old Age Pension (OAP), Health, Farmers Welfare etc. The proposed algorithm is implemented to match entries of E-governance dataset available across various public sector departments,particularly focusing regional languages of India (especially Tamil to Tamil matching and Tamil to English matching). Tamil language to Tamil language matching is carried out to avoid the redundant records, which is unique and novel contribution in processing the large scale heterogeneous datasets. Experimental results are provided to ascertain the effectiveness of the proposed algorithm along with implementation of font conversion process and a customized PostgreSQL plugin. The experimental validation of the proposed matching algorithm proves the capability of the algorithm to identify the duplicate records for the unique set of data considered for the experimental study.
Teacher’s Strategies in Teaching Speaking Skill, A Case Study on the First Grade of English Teacher at MA Terpadu Daarul Istikmal.

Emah Gujaemah, 152301850. 2019. Teacher’s Strategies in Teaching Speaking Skill, A Case Study on the First Grade of English Teacher at MA Terpadu Daarul Istikmal.This research investigate Teacher’s Strategies in Teaching Speaking Skill. It is aimed to know what strategies that teacher used in learning Speaking at the first grade students of senior high school of MA Terpadu Daarul Istikmal. The method used in this research is qualitative by using observation and interview to collect the data from research subject. The objectives of the result finding is to investigate the teacher’s strategies in teaching speaking skill and students’ responses toward the strategies used by the teacher. The result of the research revealed that teacher has used strategies in teaching speaking skill. These strategies are cooperative language learning and role play in teaching speaking skill. Cooperative did in the form the small group and discuss about introducing self, and role play teacher instruction to make mini drama in group and presentation or practice their group in front of the class. Hopefully, teacher will be able stimulate students’ responses and students’ interest in teaching learning English process especially in speaking English.
Foundation of Movie Recommendation System for Modern Day Applications

The system is a movie recommendation system which predicts the most favourable movies to a user using the user’s past behaviour . The system uses clustering algorithm to group similar movies, followed by cosine similarity and collaborative filtering to predict ratings of clustered movies in descending order that is the movie with highest rating on the top and so on.The system is best suited for users who have record of watching movies.
MEASURING INSTRUCTOR'S READINESS ON ACCEPTING THE USE OF E-LEARNING SYSTEM DURING COVID-19 PANDEMIC IN HIGHER EDUCATION OF KUWAIT

E-learning has arisen as a need to face the obstacles raised by Covid-19's current circumstance and IT growth and the capacity for greater access to information.The decision to close all educational institutions, including public and private universities, is among the difficulties faced by the State of Kuwait during the Corona pandemic.There were appeals and claims to carry out the e-learning process separately.However, several obstacles affect the implementation of e-learning in higher education.Whether various stakeholders in higher education institutions prefer to accept or oppose e-learning for their work needs to be understood.This study explores the readiness of instructors in Kuwait's higher education institutions to carry out the process of e-learning.The key purpose of this report is to evaluate Kuwait's universities instructors' readiness.To realize this research target, the e-learning literature was studied, and an exploratory analysis was performed in Kuwait.Then a conceptual model was proposed based on TAM's technological preparation model and amended with the findings of e-learning literature analysis to measure the e-learning acceptance.The initial conceptual model was developed to research e-learning readiness in Kuwait.Quantitative analysis approach was used to analyze and test the conceptual construct.Conducted a questionnaire web-based.This report ends by highlighting research's key results.
Interoceptive awareness:Metaphorical mapping & bodily experiences for insourcing tuning

The growing HCI interest in the role of the body and bodily experiences in design has led to new interactive technologies or design methods harnessing them. Despite this interest, interoceptive awareness has been limitedly explored in HCI research. This paper offers a reflection on technologies and design methods supporting interoceptive awareness that I have explored and designed with my research group, with a focus on how these may support insourcing tuning.
Using Customized Hangaroo Game for Vocabulary Teaching at SMPN 1 Bosso

Using game is one of the most fashionable techniques in teaching vocabulary. This research aims to find out whether the customized hangaroo game is effective to improve the students’ vocabulary in the eighth grade of SMPN 1 Bosso. Hangaroo game is customized to be a non-digital/offline game to meet the needs of English vocabulary teaching in that class. This research applied pre-experimental method with pre-test, treatment, and post-test design. The instrument of this research was an objective vocabulary test. The treatment of teaching vocabulary using customized hangaroo game was conducted in five meetings. The data from the tests were analyzed using quantitative procedures including statistical analysis using SPSS 22. The results show that using customized hangaroo game is effective in improving the students’ vocabulary mastery at the eighth grade of SMPN 1 Bosso. The students’ mean score the pre-test was 36.4783 (poor) while in post-test was 51.6957 (fair). From the t-test of the students’ vocabulary, p value was smaller than α (0.00<0.05). The customized hangaroo game could interest and motivate the students in learning vocabulary. It can help the students to develop their spelling and pronunciation. It can also facilitate the students to cooperate in group and share to class.
Library Guides: EBSCOHOST Database: How to download E-Book

This guide has been designed to assist the students towards navigating around the databases
Automated Guided Vehicle Using Kinect Sensor

In this project, we present a gesture human action recognition system for the development of a human-robot interaction (HRI) interface. Kinect cameras and the other sensor combination framework are used to obtain real-time tracking of a human action skeleton. Different gestures, performed by different persons, Quaternion’s of joint angles are first used as robust and significant features. Next, neural network (NN) classifiers are trained to recognize the different gestures. This work deals with different challenging tasks, such as the real-time implementation of a gesture human action recognition system and the temporal resolution of gestures. The HRI interface developed in this work includes three Kinect and robot that can be remotely controlled by one operator standing in front of one of the Kinect sensor. Moreover, the system is supplied with a people action for control of the robot.
LibGuides: GIS for Elementary Curriculum: Home

GIS is at the forefront of the next wave of technology in the business world. GIS is used for e911 systems, Ethernet (5G) address validation systems, and even in city development. It is time to bring GIS into the classroom. In the guide, you will find
A method for avoiding obstacles of a self-driving carin the dynamic environment based on model predictive control

The paper discusses the problem of obstacle avoidance of a self-driving car in urban road conditions. The artificial potential field method is used to simulate traffic lanes and cars in a road environment. The characteristics of the urban environment, as well as the features and disadvantages of existing methods based on the structure of planning-tracking, are analyzed. A method of local path planning is developed, based on the idea of an artificial potential field and model predictive control in order to unify the process of path planning and tracking to effectively cope with the dynamic urban environment. The potential field functions are introduced into the path planning task as constraints. Based on model predictive control, a path planning controller is developed, combined with the physical constraints of the vehicle, to avoid obstacles and execute the expected commands from the top level as the target for the task. A joint simulation was performed using MATLAB and CarSim programs to test the feasibility of the proposed path planning method. The results show the effectiveness of the proposed method.
Lossless Compression of Efficient Private Local Randomizers

Locally Differentially Private (LDP) Reports are commonly used for collection of statistics and machine learning in the federated setting. In many cases the best known LDP algorithms require sending prohibitively large messages from the client device to the server (such as when constructing histograms over large domain or learning a high-dimensional model). This has led to significant efforts on reducing the communication cost of LDP algorithms. At the same time LDP reports are known to have relatively little information about the user's data due to randomization. Several schemes are known that exploit this fact to design low-communication versions of LDP algorithm but all of them do so at the expense of a significant loss in utility. Here we demonstrate a general approach that, under standard cryptographic assumptions, compresses every efficient LDP algorithm with negligible loss in privacy and utility guarantees. The practical implication of our result is that in typical applications the message can be compressed to the size of the server's pseudo-random generator seed. More generally, we relate the properties of an LDP randomizer to the power of a pseudo-random generator that suffices for compressing the LDP randomizer. From this general approach we derive low-communication algorithms for the problems of frequency estimation and high-dimensional mean estimation. Our algorithms are simpler and more accurate than existing low-communication LDP algorithms for these well-studied problems.
An Empirical Study on the Exchange Rate Volatility of Shanghai Cooperation Organization Countries Based on Computer Software Analysis

Abstract With the rapid development of our economy, the market of economic exchange rates between our country and other countries has also fluctuated. This paper analyzes the volatility of exchange rates among members of the Shanghai Cooperation Organization. The result shows that the economic volatility and exchange rate volatility among its members have strengthened gradually, and the courseware Shanghai Cooperation Organization has been developing steadily.
Distribution of the First Alert Range for Low UA Speed Encounters

This presentation shows the percentage of encounters that receive full corrective alerts as a function of the surveillance range.
THE FORMATION OF SPEECH COMPETENCE

Speech activity is the basis of pedagogical activity and in the competence model of the future teacher is a systemic component. Therefore, speech competence comes to the fore as a personality quality that is formed in speech activity and is considered as an indicator of the quality of education. This article presents the essential characteristics of the speech competence. The speech competence is defined as a set of interrelated personality traits (knowledge, skills and ways of life) defined in relation to a specific component of speech preparation.
Identity-Based Data Outsourcing with Comprehensive Auditing in Cloud-Based Healthcare Applications

Portable cloud computing (MCC) permits versatile clients to have on-request access to cloud administrations. The versatile cloud model in which the data concerning the patients’ records is broke down, and it can separate proposals. Since the human services applications want progressively more calculation and correspondence assets, these need access to more information inside and beyond an association as well. In compact appropriated registering, a fine-grained level access control of multi-server cloud data is a pre-basic for the successful execution of end customers’ applications. In our proposed system, another arrangement that gives a combined technique of fine-grained gets the opportunity to control over cloud-based multi-server data nearby a provably secure versatile customer affirmation segment for the Healthcare. The proposed paradigm is, as far as we can see, first one to search for fine-grained information in a multifaceted, dispersed computer situation over different cloud servers.
MIF: Toward Semantic-Aware Representation for Video Retrieval

Semantic Concept-Based Video Retrieval (SCBVR) has been widely studied recently, which exploring semantic representations of videos to execute user’s retrieval requests. However, the effectiveness of video retrieval often depends on the accuracy of semantic concepts, but the semantic concept is often imprecise or contrary to the ground-truth. In order to solve the above-mentioned problem, we propose a novel multi-information fusion (MIF) approach, and it is beneficial to improving the performance of video retrieval. Firstly, we infer the most relevant semantic concept corresponding to query keywords by using the inherent association information of videos. Secondly, we fuse the probabilities of the candidate semantic concept by minimizing the potential function. We conduct the extensive experiments on real-world datasets which demonstrate the effectiveness and efficiency of the proposed approach for enhancing the performance of video retrieval.
Identification of Fake VS Original logos using Deep Learning

Logo or trademark conveys the significance of an organization or a product. In view of determining of the authenticity of a logo, a precise extraction of features is crucially important for any automated recognition system to succeed. Here in this proposed work, identification of fake logos are done by fusion based approach of features from SIFT and SURF which considerably does better compared to the existing methods.
Articulating Musical Practice and Research

Recent changes in South African government legislation have allowed for formal recognition of creative outputs such as live performances, recordings and compositions. Applying the tenets of systems theory to musical undertakings, I take a recent recording of a composition of mine as an example of such an output. Despite my identification as the composer of the piece, I argue that its realization was a collective effort in which the ensemble responded to cues from myself and the other participants to bring the piece to life. The piece is designed to accommodate real-time contributions in the sense that it has a very open structure. The question still remains as to how such a composition might articulate with ethical concerns such as the nature of teamwork and ownership.
LibGuides: Victim and Survivor Resources: Stay Connected and Safe

This guide is an evolving resource for anyone seeking help or information and is an extension of the physical displays that are periodically showcased in the library.
The essence of professional competence for foreign language teaching

The concept of ‘competence’ is related to the notion that all professional processes need to be considered and that there is a lot of collaboration in the pedagogical context and that the participants in the learning process need to acquire. Therefore, competence is a way of behaving in different professional situations, communicating, new behaviors in relationships, unclear tasks when working with competitors, use of information full of contradictions, adapting to a plan of work in evolving and complex processes . Professional competence is defined not by the acquisition of skills, but by the knowledge of a specialist, which implies the acquisition of independent independent knowledge and actions in each field, constantly enriching the knowledge of competence specialization, learning new works to understand social problems, seeking new edits, it requires the ability to process them and work in their own activities. The purpose of this article is to clarify the concept of competence and the essence of professional competence, as well as to review the cases of professional competence, to clarify its structure and capabilities, as well as to highlight the professional competencies and skills that foreign language teachers should possess. In expressing such things and illuminating the components, the ideas are generalized using diagrams and tables as well as work done earlier.
Preliminary Analysis of Ground-Based Measured Solar Data From Sauran Sta Station at Umlazi, South Africa

The growing worldwide demand of electricity and the consequences related to the use of fossil fuel to generate electricity have boosted research in renewable and sustainable energies to overcome those challenges. From diverse sources of renewable energies (RE), solar and wind are wildly distributed and have reached the maturity stage. South Africa (SA) as one of growing economy is in need of more electricity to sustain its domestic need of electricity and its economy, RE is an option. With its potential in solar energy (SE), the need of accurate information on site to build solar power plans are of vital importance for designers and decision’s makers. This paper presents the preliminary analysis of ground-based measurements solar data in Umlazi, South Africa. From this analysis, data statistics and statistic models for the global horizontal irradiance (GHI), the direct horizontal irradiance (DHI) and the ultraviolet radiations (UVR) are obtained for Durban and surrounding areas. Those results can be used in the design and analysis of solar systems and can also be used as referential parameters for further assessment of solar energy potentials for those areas.
General Risk Literacy Skills are Causally Related to Improved Self-Evaluations: Training Graph Literacy Improves Decision Making and Lowers Overconfidence

Overconfidence commonly refers to a cognitive bias in which people express more subjective confidence in their abilities than can be objectively justified. Similarly, the “Unskilled and Unaware” literature demonstrates that individuals who are lowest in experience or knowledge are often the most overconfident. Further, recent research on decision aids and training programs suggests that improving task-specific skills can causally reduce task-specific overconfidence biases. However, these training benefits do not appear to transfer or otherwise reduce overconfidence on untrained judgment tasks more generally. One important example of general training is Morewedge et al. (2015), where training specific decision biases (e.g., confirmation bias) led to reduced overconfidence for better-than-average overconfidence effects. While these findings are promising, research has not yet investigated the potential benefits of programs designed to train general decision making skills, such as risk literacy skills (i.e., the ability to evaluate and understand risk; See Cokely et al., 2018). Accordingly, I report results from the first experimental study to test the benefits of an online risk literacy tutor (tutor.lolevo.com) designed to improve graph literacy skills (e.g., interpreting bar, pie, line, icon arrays, and decision tree graphs). Statistical and structural modeling results revealed that the graph literacy tutor causally improved graph literacy skills, which in turn causally reduced biases on several untrained, conceptually distinct decision tasks (framing effects, ratio bias, and sunk costs). Moreover, improvements in graph literacy also transferred benefits to untrained overconfidence measures, causally improving self-evaluations on the untrained decision tasks. Consistent with Skilled Decision Theory, results indicated that risk literacy skills are trainable and are related to general decision making skills. Further, results suggested that training risk literacy skills could have implications for an abundance of risky situations (e.g., Covid-19 risk knowledge, heart attack symptom recognition) because training risk literacy can reduce many kinds of decision biases, including multiple types of potentially trainable overconfidence biases (e.g., overestimation, overprecision, overplacement). In addition to other theoretical implications, it is noteworthy that the current study appears to be the first to discover a direct causal link between risk literacy skills and valuable metacognitive skills. Risk literacy skills causally promote skilled self-evaluation and accurate social comparisons.
Interaction-Grounded Learning

Consider a prosthetic arm, learning to adapt to its user's control signals. We propose Interaction-Grounded Learning for this novel setting, in which a learner's goal is to interact with the environment with no grounding or explicit reward to optimize its policies. Such a problem evades common RL solutions which require an explicit reward. The learning agent observes a multidimensional context vector, takes an action, and then observes a multidimensional feedback vector. This multidimensional feedback vector has no explicit reward information. In order to succeed, the algorithm must learn how to evaluate the feedback vector to discover a latent reward signal, with which it can ground its policies without supervision. We show that in an Interaction-Grounded Learning setting, with certain natural assumptions, a learner can discover the latent reward and ground its policy for successful interaction. We provide theoretical guarantees and a proof-of-concept empirical evaluation to demonstrate the effectiveness of our proposed approach.
Pengembangan Bahan Ajar Menulis Deskripsi Menggunakan Model Circuit Learning pada Siswa Kelas VII SMP di Samarinda

Research on the development of teaching materials for writing descriptions using the learning model of Circuit learning needs to be done because teachers and students have difficulty learning the process of writing descriptions. This study aims (1) to find out the process of developing teaching materials in writing descriptions by using the Circuit Learning model (2) to measure the quality of teaching materials writing descriptions using circuit learning methods assessed from the validity and effectiveness. This study applies research and development methods conducted at Nabil Husen Middle School Samarinda. The results of development research can be seen from the validation results, namely material validation with a value of 88, graphic validation with a value of 86 and a validation of language values ​​with a value of 97 with very valid criteria. The effectiveness test results seen from the implementation of the lesson plan, the teacher's response value 93, the students' response value 93 and the value of the description writing test results obtained an average value of 88 with very effective criteria. Thus, the research development of teaching material writing descriptions by using the learning model of circuit learning in class VII students is very valid and effective.