Reviewerly/exHarmony huggingface dataset:
Mining Rules From Distributed Big Data Repositories: A Novel Scheme Fo Valuable Association Rule Detection

Rapid advancements made in technology have increased the growth of information on the internet. It becomes a challenging process for the users to suggest the right decision at the right time.  The real-time issues are to be explored. It is observed that some items are not classified properly and thus leads to improper recommendation processes under a different context.  Henceforth, the enhancement of the contextual information will improve the performance of the distributed databases. In our research study, this scalability of big transactional database issues is resolved by proposing a novel consistent and inconsistent rule detection using frequent pattern mining under a big data context. The big sales data is collected from a public repository and’s preprocessed by the elimination of null transactional records in the databases. Then, it is formulated as zone-wise transactional databases. The apriori algorithm is employed to find out the patterns which are frequent from the sales data. With the estimated interestingness value, the rules are framed, detected, and classified into consistent and inconsistent rules for each zone. Experimental results have shown the efficiency of the proposed technique.
MANAGEMENT OF ICT-MEDIATED LEARNING: A CURRICULUM DESIGN PROPOSAL FROM UNIVERSIDAD NACIONAL DE CHIMBORAZO

The current situation in the field of education demands teachers who are capable of functioning in new learning scenarios where the possibilities offered by ICT for information acquisition and communication processes are enormous. In this sense, it is necessary to have postgraduate programs that contribute to the development of digital skills in teachers. The main purpose of this work is to propose the curricular design for a Master's program in Education, Mention in Management of Learning Mediated by ICT, offered by Universidad Nacional de Chimborazo in Ecuador. For this, a qualitative research was undertaken in order to characterize and determine the most important features of each module of the curriculum. A documentary research design was applied through the PICOC method (Population, Intervention, Comparison, Outcome, Context). The result of this work was a curricular mesh that consists of 12 study modules wherein aspects such as: digital literacy for the new society were addressed; didactics in new digital environments; the design and development of content and digital resources for learning; new ways of learning and innovating in education; as well as research in educational technology.
PENGARUH MODEL PEMBELAJARAN KOOPERATIF TIPE TEBAK KATA DAN KELILING BERKELOMPOK TERHADAP HASIL BELAJAR SISWA PADA MATA PELAJARAN IPS DI KELAS VIII SMP NEGERI 2 KOTA JAMBI

Abstract This study aims to determine the learning outcomes of students who are taught using a cooperative learning model type Guess the word and group around in social studies subjects in class VIII SMP Negeri 2 Jambi City and a comparison of the cooperative learning model type Guess the Word and Go Around Groups on student learning outcomes in the subject. Social Studies lessons in Class VIII SMP Negeri 2 Jambi City. The type of research conducted is a quasi-experiment. The guessing type cooperative learning model for class VII C (control) and the group traveling type cooperative learning model for class VIII B (experimental). Sampling in this study used purposive sampling technique, so that 38 students of class VIII C were selected as the control class and 32 students of class VIII B as the experimental class. Data collection techniques are carried out by distributing questions to research respondents and documentation. The data analysis technique used the t-test. The results showed that the average value of posttest learning outcomes for class VIII B (experimental class) was 10,063 and the average value for learning outcomes for social studies subjects in the posttest stage in class VIII C was 8.079. Based on these results, the average value of learning outcomes for social studies subjects at the posttest stage in class VIII B is higher than class VIII C. The results of the t-test show a t-count value of 8.480 and a significance value of 0.000 <0.05, so H0 is rejected. and Hadi Accept. Based on these results, the cooperative learning model type Guess the Word and Go Around in Groups has an effect on student learning outcomes in social studies subjects in Class VIII SMP Negeri 2 Jambi City. Keywords: Cooperative Learning Model Type Guess the Word and Mobile Group, Learning Outcomes
Design of Automatic Dry Waste Segregation System

Currently, about 2.01 billion metric tons of Municipal Solid Waste (MSW) are produced annually worldwide. The World Bank estimates overall waste generation will increase to 3.40 billion metric tons by 2050. With such huge amounts of waste being produced, management and disposal of waste become a herculean task. Moreover, the waste produced has many materials which may be reused profitably. A solid waste management system not only solves the problem of efficient disposal but also helps in recycling & reusing important resources. This also helps in reducing the impact of modern society & its needs on the environment. India alone produces a staggering 62 million tonnes of waste of which 43 million tonnes is collected and merely 11.9 million tonnes is treated (less than 20%)! The rest of the waste ends up in landfills which not only pollute the environment but also increase the need for importing many raw materials for Indian industries from other countries. The current waste management practice in India involves collecting waste from sources through a community collective bin system, after which it gets transported to a low-lying landfill system with intermediate processing of Municipal Solid Waste (MSW). The open dumping practice is leading to various problems like pollution and health hazards. Both surface and groundwater are affected by this; in fact, groundwater is in a critical state. Current procedures are not ideal, hence, India is facing a solid waste management crisis. The study and research conducted in this project will tackle the above-mentioned problems at the ground level while maintaining the highest level of possible effectiveness and mainly making the process automated and inexpensive. With the presence of a simple and inexpensive setup, we believe that such a system will be easy to integrate into the present waste management scenario at a considerably low cost and hence will try to tackle the solid waste management crisis faced by Indian and many other countries worldwide.
A Text Analytics Approach to Study Python Questions Posted on Stack Overflow

Stack Overflow (SO) is one of the largest discussion platforms for programmers with different technical backgrounds to discuss and communicate their ideas and thoughts related to various topics, including but not limited to software development and data analysis. Many programmers are actively contributing to this platform and discuss about Python programming language, which is one of the most popular programming languages used for data analysis. To better study the topics related to Python questions posted on the platform, a text analytics approach incorporating text preprocessing steps and Latent Dirichlet Allocation (LDA) topic modelling algorithm is proposed to study and analyze Python questions posted on SO from 2008 to 2016. The two main objectives of this study are: to discover and analyze the topics of the questions about Python programming language posted on SO from 2008 to 2016 to identify and compare the topics being discussed in each year, and to analyze questions about Python programming language with high votes posted on SO from 2008 to 2016 using topic modelling technique with a suitable number of topics. Based on the study, we find that the topics of the Python questions posted on Stack Overflow have gradually shifted towards those related to data modelling and analysis from 2008 to 2016. Furthermore, the study also shows that a suitable number of topics using the topic modelling technique yield a high coherence score concerning the topic model in use, which is important to extract more meaningful topics from the collection of Python questions. A topic model with 8 topics can be used to extract more meaningful topics from Python questions with high votes posted on SO from 2008 to 2016.
Aline Godfroid: Eye tracking in Second Language Acquisition and bilingualism. A research synthesis and methodological guide

Article Aline Godfroid: Eye tracking in Second Language Acquisition and bilingualism. A research synthesis and methodological guide was published on November 1, 2021 in the journal Folia Linguistica (volume 55, issue 2).
لتشع تونس من جديد

This book investigates the socioeconomic factors that triggered Tunisia’s for dignity” and the current issues and challenges facing its economy while suggesting mechanisms and instruments for their resolution. The author begins by analyzing the roots of the revolution and the post-revolution situation from a political sociology perspective and then diagnoses the Tunisian economy before and after the revolution and identifies the multidimensional binding constraints preventing it from escaping the middle-income trap. The book then explores the pillars of an inclusive development strategy that Tunisia should pursue. The emphasis is made on building inclusive institutions, developing a new social contract and reinventing the country's leadership. Beyond the institutional dimension, the author suggests innovative financial channels, discusses the strategy of a successful integration of the Tunisian economy in the global economy as well as the pillars of its transformation into a knowledge-based economy.
Las experiencias en la formación posgradual de la especialización en pedagogía y didáctica que sensibilizan la práctica docente

The aim of this article is to understand the experiences in postgraduate training in pedagogy and didactics and how the development of the whole training process is generating self-reflection and deep reflections in front of others, new social and particular contexts in our teaching practice, In addition to how the methodologies developed in training lead to critical-reflective thoughts of the educational work, since being aware our experiences implies recognizing what affects us and building our own knowledge that later, sensitizes the teaching practice because there is a redefinition of the way to do the things. In the end it is intended to clarify conclusively how these personal stories, and the importance of delve deeper into these studies, and the importance of delving deeper into these studies, lead to the knowledge and experimentation of doing better what we do in the classroom.
“To Read What Was Never Written”

Benjamin’s assertion that we can “read what was never written” evokes one of the foundational sources of Western epistemologies – reading – and challenges its supremacy. Benjamin urges us to consider other forms of knowledge and communication beyond that which we can put into words on a page. Texts, for him, do not simply consist of the tomes with which we line our bookshelves, but should also be recognised in other forms such as our movements, our emotions, and our environment. Expanding our understanding of texts in this way is central to my approach to pedagogy. I argue that we need to take our embodied selves in the classroom seriously, and that doing so fundamentally changes how we approach learning and teaching. Moreover, this commitment affects our relationship with the university more broadly, from how we conceptually approach learning and teaching to how we respond to (and should design) the physical environment in which we meet each other and our students. In this chapter, I focus on what it might mean for an instructor to embrace embodiment, and to share some of the ways my pedagogy reflects this commitment. First, I identify some of the key issues with current approaches to learning and teaching in higher education and suggest that we should be more responsive to students as their whole selves. I then explore what it means to take embodiment seriously by considering three locations of embodiment in the university: space and place; the student’s body; and the professor’s body.
TSG: Target-Selective Gradient Backprop for Probing CNN Visual Saliency.

The explanation for deep neural networks has drawn extensive attention in the deep learning community over the past few years. In this work, we study the visual saliency, a.k.a. visual explanation, to interpret convolutional neural networks. Compared to iteration based saliency methods, single backward pass based saliency methods benefit from faster speed and are widely used in downstream visual tasks. Thus our work focuses on single backward pass approaches. However, existing methods in this category struggle to successfully produce fine-grained saliency maps concentrating on specific target classes. That said, producing faithful saliency maps satisfying both target-selectiveness and fine-grainedness using a single backward pass is a challenging problem in the field. To mitigate this problem, we revisit the gradient flow inside the network, and find that the entangled semantics and original weights may disturb the propagation of target-relevant saliency. Inspired by those observations, we propose a novel visual saliency framework, termed Target-Selective Gradient (TSG) backprop, which leverages rectification operations to effectively emphasize target classes and further efficiently propagate the saliency to the input space, thereby generating target-selective and fine-grained saliency maps. The proposed TSG consists of two components, namely, TSG-Conv and TSG-FC, which rectify the gradients for convolutional layers and fully-connected layers, respectively. Thorough qualitative and quantitative experiments on ImageNet and Pascal VOC show that the proposed framework achieves more accurate and reliable results than other competitive methods.
Pelatihan Pembuatan Soal Menggunakan Google Formulir Di SDN Batangkaluku

This community service is carried out with the aim of increasing the knowledge and skills of teachers in utilizing the Google Forms application in question-making activities. This community service was carried out in November 2020. The implementation of this community service was carried out using the presentation, training, and evaluation methods. The conclusions obtained through this community service activity are; 1) improve the knowledge and understanding of teachers at SDN Batangkaluku about the Google Forms application, 2) improve the ability of teachers at SDN Batangkaluku in making questions using the Google Forms application.Keywords: Training, Questions, Google Forms
ZeroWaste Dataset: Towards Deformable Object Segmentation in Extreme Clutter.

Less than 35% of recyclable waste is being actually recycled in the US, which leads to increased soil and sea pollution and is one of the major concerns of environmental researchers as well as the common public. At the heart of the problem are the inefficiencies of the waste sorting process (separating paper, plastic, metal, glass, etc.) due to the extremely complex and cluttered nature of the waste stream. Automated waste detection has great potential to enable more efficient, reliable, and safe waste sorting practices, but it requires label-efficient detection of deformable objects in extremely cluttered scenes. This challenging computer vision task currently lacks suitable datasets or methods in the available literature. In this paper, we take a step towards computer-aided waste detection and present the first in-the-wild industrial-grade waste detection and segmentation dataset, ZeroWaste. This dataset contains over 1800 fully segmented video frames collected from a real waste sorting plant along with waste material labels for training and evaluation of the segmentation methods, as well as over 6000 unlabeled frames that can be further used for semi-supervised and self-supervised learning techniques, as well as frames of the conveyor belt before and after the sorting process, comprising a novel setup that can be used for weakly-supervised segmentation. Our experimental results demonstrate that state-of-the-art segmentation methods struggle to correctly detect and classify target objects which suggests the challenging nature of our proposed real-world task of fine-grained object detection in cluttered scenes. We believe that ZeroWaste will catalyze research in object detection and semantic segmentation in extreme clutter as well as applications in the recycling domain. Our project page can be found at this http URL
Study of the effect of acoustic sound bridges on wind instruments: Perceptual study with a panel of trumpet players

The study of the quality of a musical instrument, as perceived by the musician, is a complex problem. Many subtle phenomena are involved and several devices, or materials, are proposed to musicians, with a noticeable commercial success for some of them. We are interested in a particular device: sound bridges for wind instruments (made of two plates, clipped at a joint of a wind instrument with a rubber band). The objective of the work is to study if audible differences, due to the presence of the sound bridges, can be highlighted during trumpet playing. An ABX test was carried out with a panel of 5 skilled trumpet players with various status (from amateur to professional) and various use degrees of the bridges in their practice (from always to not-user). After a training phase, musicians were blinded and asked to answer to several repetitions of an ABX test in free playing conditions. Results were analyzed with the binomial distribution and the Signal Detection Theory (SDT). In addition, several repetitions of different notes were blind recorded with and without the bridges. A spectral analysis was carried out to test whether or not a significant effect of the acoustic bridges can be highlighted.
COMPARATIVE ANALYSIS EXPERT SYSTEM OF CERTAINTY FACTOR METHOD WITH DEMPSTER SHAFER METHOD BY USING OPEN DECISION MAKER TOOL FOR TODDLER AT VACCINE HOUSE

Expert system is a form progress of Information and Communications Technology. Development of an expert system can be performed in variety areas, including health. In its development required a result can be trusted by the user. Therefore it required the value of belief for any decision issued by the expert system. In expert system, there are several uncertainty methods can be used namely Certainty Factor, Dempster Shafer, Naive Bayes, Fuzzy Logic, etc. Therefore, in this study will be performed the comparison between Certainty Factor and Dempster Shafer method using data infectious diseases in toddler. Both of methods have different ways of working in the calculation, but both are equally give results to support a decision. In the comparative analysis of both methods will be used a decision support system tool namely Open Decision Maker with Analytical Hierarchy Process approach. From the comparison result of eight cases has been obtained that the Certainty Factor method have more higher belief values as big as 82.54% than Dempster Shafer method as big as 17.46%, but significantly the value of belief between the two was not differ greatly.
A Comparative Study Between China and Malaysia: Investigating the Influence of First Language (L1) Syntax in Speaking English (L2) among Primary School Students

For Malaysian students, speaking in English is one of the most challenging skills to master, especially if they do not have a strong command of the language. Meanwhile in China, the English language is primarily employed as a means of academic communication and teaching. This paper aims to identify which linguistic items have been transferred positively and negatively from L1 (Bahasa Melayu and Mandarin) in speaking English (L2) among primary school students. A qualitative study among primary school students from China and Malaysia was carried out using purposive sampling. Based on the findings, four types of syntactic errors from the Malaysian students' speech were identified. It was evident that the students had difficulties to speak correctly in terms of sentence structure. The four syntactic errors found are simple past, simple present, verb ‘to be’ and subject-verb-agreement. Meanwhile, it has been found that Chinese students frequently produce linguistic mistakes during their utterances of L2 speech as a result of L1 interference. This research also exposed that the students are still unconsciously relying on their mother tongue to translate their sentence into L2. The study is expected to help ESL teachers to draw the analogies between corresponding L1 and L2 syntax constructions. The findings will contribute and direct the learners’ attention to cross-language syntactic similarities and differences and thus guide them to a deeper understanding of underlying linguistic structure.
A survey of Two Factor Authentication Methods : Advantages & Disadvantages

Authentication forms an important step in any security system to allow access to resources that are to be restricted. In this paper, we compare the advantages and disadvantages of two authentication methods. We begin with the details of existing systems in use and then compare the two systems viz: Two Factor Authentication (2FA), Risk-Based Two Factor Authentication (RB-2FA). We also introduce a new variation of the risk based two factor authentication system called the artificial-intelligence assisted two-factor authentication.
Shielded Computations in Smart Contracts Overcoming Forks

In this work, we consider executions of smart contracts for implementing secure multi-party computation (MPC) protocols on forking blockchains (e.g., Ethereum), and we study security and delay issues due to forks. In this setting, the classical double-spending problem tells us that messages of the MPC protocol should be confirmed on-chain before playing the next ones, thus slowing down the entire execution.
Integrating the Case Method in Transportation and Logistics Education

This paper describes what is involved in learning through using the case method, with particular emphasis on transportation education. The case method calls for discussion of real life situations that have been faced by transportation managers or executives. Cases approximate the kinds of situations that students would encounter in a managerial role. These situations have been prepared by casewriters, who have sought good reporters to present the information available to the manager or executive concerned. For the covering abstract of this conference see IRRD number 872753. (A)