Reviewerly/exHarmony huggingface dataset:
Priority-Aware Per-flow Measurement using Cuckoo Sketch

Flow size estimation is a key task in per-flow measurement. In real scenarios, among millions of flows, people are often particularly interested in a small subset of given flows. These flows with high priorities are called important flows. In this poster, we propose the Cuckoo sketch, which provides higher accuracy for important flows. The key idea of the Cuckoo sketch is to separate the important flows from the unimportant ones and store them in different structures: the important flows are stored in a Cuckoo hash table where the exact size of the flow is stored while the unimportant flows are stored in a Count-Min sketch. The reallocation mechanism of the Cuckoo hashing is used to make some space in the Cuckoo hash table for the important flow by evicting the ones that are less important, which leads to a slight loss in throughput. Experimental results show that Cuckoo sketch provides better accuracy on important flows, reducing the average relative error by up to 69%, with only suffering from a negligible loss in accuracy for unimportant flows.
Workshop 17: PAISE Parallel AI and Systems for the Edge

Applications involving voluminous data but needing low-latency computation and local feedback require that the computing be performed as close to the data source as possible — often at the interface to the physical world. Communication constraints and the need for privacy-preserving approaches also dictate the need for computing at the edge. Given the growth in such application scenarios and the recent advances in algorithms and techniques, machine learning and inference at the edge are unfolding and growing at a rapid pace. In support of these applications, a wide range of hardware (CPUs, GPUs, ASICs) is venturing farther away from the center, closer to the physical world. The resulting diversity in edgecomputing hardware in terms of capabilities, architectures, and programming models poses several new challenges.
R2DCLT: retrieving relevant documents using cosine similarity and LDA in text mining

The availability of digital documents over web has increased exponentially and hence there is a need for effective methods to retrieve and organise. Since data is dispersed globally and unorganised, a number of algorithms have been proposed based on relevance calculations. However, it is found that there is a gap between user's search intention and retrieved results. In this paper, we propose a framework for retrieving relevant documents using cosine similarity (CS) and LDA in text mining (R2DCLT). The uniqueness of this approach is that LDA is applied for the documents and extracted patterns like unigram, bigram and trigram. Documents are ranked based on the CS score. Experiments are conducted on Reuters Corpus volume and custom news dataset. It is observed that R2DCLT outperforms pattern taxonomy and relevance feature discovery models by providing high quality relevant documents with improved response time and dynamically updated document set.
Managing uncertainty during CBR systems vocabulary maintenance using Relational Evidential C-Means

Due to the incremental learning of Case-Based Reasoning (CBR) systems, there is a colossal need to maintain their knowledge containers which are (1) the case base, (2) similarity measures, (3) adaptation, and (4) vocabulary knowledge. Actually, the vocabulary presents the basis of all the other knowledge containers since it is used for their description. Besides, CBR systems store real-world experiences which are full of uncertainty and imprecision. Therefore, we propose, in this paper, a new policy to maintain vocabulary knowledge using one of the most powerful tools for uncertainty management called the belief function theory, as well as the machine learning technique called Relational Evidential C-Means (RECM). We restrict the vocabulary knowledge to be the set of features describing cases, and we aim to eliminate noisy and redundant attributes by taking into account the correlation between them.
Personalizing persuasive technologies workshop 2020

Research has shown that personalizing persuasive technologies can increase their effectiveness and potentially leads to sustained behavioral change. Building on the success of the workshop in the past four years which attracted 100s of participants from over 20 different countries and led to a special issue, this year's workshop will further advance the research area by addressing outstanding challenges and opportunities identified during the previous workshops and developing a new focus areas for the field. The workshop aims to connect a diverse group of researchers and practitioners interested in personalization and tailoring of persuasive technologies. Attendees are encouraged to share their experiences, ideas, discuss key challenges facing the area, and discuss how to move the field forward. The workshop will cover broad areas of personalization and tailoring, including but not limited to personalization models, computational personalization, design and evaluation methods, and personalized persuasive technologies. We welcome submissions and ideas from any domain of persuasive technology and HCI including, but not limited to health, sustainability, games, safety and security, marketing, eCommerce, entertainment, and education. Workshop papers and ideas will be archived online to be accessible to the general public.
Goalpost Detection Using Omnidirectional Cameras on ERSOW Soccer Robots

The ERSOW robot is a soccer robot developed by Politeknik Elektronika Negeri Surabaya, Indonesia. One important ability of a soccer robot is the ability to find the goal in the field. Goal Post is often used as a sign by soccer robots in a match. The mark is a reference robot in the field to be used in determining the strategy. By knowing the location of the goal in a field, the soccer robot can make the decision to maneuver in the match to get the right goal kick. There are various methods of detecting goal. One of them is to detect goal post using vision. In this study the radial search lines method is used to detect the goalposts as markers. Image input is generated from an omnidirectional camera. The goal area that is detected is the front side of the goal area. With experiments from 10 robot position points in the field, only 1 position point cannot detect the goal. The robot cannot detect the goal because what is seen from the camera is the side of the goal, so the front side of the goal area is not visible.Keywords— omnidirectional camera, vision, radial search lines, goal detection, ersow soccer robot
Implementing School Policy: Teachers’ Strategies in Improving Students Speaking Ability

The problem of learning language skills especially speaking still exists in many educational&#x0D; institutions in Indonesia. For schools and English teachers, overcoming this problem becomes a huge&#x0D; challenge because Indonesian learners still underestimate the capability of formal educations also&#x0D; English teachers to educate them in the right way. This research will investigate the school's policy&#x0D; and the teachers' strategies in improving students' speaking ability in a Bilingual High School in&#x0D; Indonesia. The research questions to be are what the school policy is on improving students'&#x0D; speaking ability, what the teachers' strategies are in implementing the school policy to improve&#x0D; students' speaking ability. A case study is employed for this research. The data of this research is&#x0D; taken from an in-depth interview with English teachers and school officials, observation, and&#x0D; documentation. The techniques of data verification in this research are using triangulation technique&#x0D; and member check. The purposes of this research are to show the positive teachers’ strategies in&#x0D; implementing school policy in improving students’ speaking ability.
Architecture Optimization and Interpretability in Neural Networks for HRTEM Segmentation

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Redesign and Improvement of Pottery Spinner to Increase Worker Producivity

Many small industries produce handicrafts related to art in Bali, one of which is pottery. Pottery is an object made of clay which is formed and then burned to be a unique shape such as: jugs, glassware, cauldron, brazier, piggy bank, and other objects. The process of producing pottery required the complex steps, from preparing clay, printing by turning, drying and burning. The main difficulty of pottery producers is in the process of forming shapes which involved the rotating spinner. Most of small industries still use the manual spin control to rotate clay bucket holder. This research aims to re-design of a rotating spin machine from the existing pottery industries to increase the productivity. The sample was overtaken from 12 craftsmen in Singakerta Village, District of Ubud Gianyar, Bali. Sample P0 was given to craftsmen is still used the old design and P1 was given to sample modified and re-designed the old machine with added automatic control of rotating spinner. Workload is calculated based on the worker's pulse rate which is measured using a pulse meter. Research data were analyzed using descriptive and inferential statistics. T-test method was performed to analyzing the differences range between groups P0 and P1 at significance level of 5%. The results showed a workload was decreased from heavy to moderate by 12.09%. Production rate was increased by 282.1%, and productivity increased by 334.6%
Perancangan Aplikasi Data Mining Penjualan Menggunakan Metode Clustering Pada Toko Pon Prima Pass

Rapid growth of the accumulated data has created the conditions for data-rich but information will be minimal. Data mining is the mining or the discovery of new information by searching for patterns or certain rules of a number of large amounts of data are expected to treat the condition. This research resulted in the application from the application of data mining to read the pattern of stock items. Data collection techniques used are observation interview and documentation study. Device tools analyst is flowchart  and UML. Methods of analysis and design software using the method waterfall development model. The design of this application using PHP with a MySQL database. This application uses data mining with methods of clustering and k-means algorithm to process the reading patterns of purchasing goods. By forming patterns based on with goods that have been sold, to then seek the value of the support and confidence of two or more different items for the shop owner into consideration in making a decision. Along with the above problem, data mining is able to create business environment a smart to deal with increasingly high rates of business competition souvenir Pon Prima Pass in the future.
THE IMPORTANCE OF INFORMATION AND COMMUNICATION TECHNOLOGIES (ICTS) IN ZIMBABWE: A CASE STUDY OF SOCIAL MEDIA IN THE TOURISM AND HOSPITALITY SECTOR.

The Postal and Telecommunications Authority of Zimbabwe (POTRAZ) statistics point to the rise in the use of social media in Zimbabwe.The United Nations World Tourism Organisation(UNWTO) also allude to the important role played by the tourism industry in the economic development and growth around the world.This study sought to find a nexus between the exponential rise in usage of social media and its impact on the tourism and hospitality in Zimbabwe which ultimately could contribute to the economic growth of the country.The research set out to focus on establishing from tourists, the influence of social media in the choice of tourist destinations as well as to determine the role of social media as a marketing tool from players in the tourism and hospitality sector.Other objectives were to identify popular social media platforms as well as the benefits and challenges arising out of the use of social media in the industry.The qualitative research methodology was used for the study where face to face and telephonic interviews as well as in-depth emailed questionnaires were used to as data collection instruments using a purposive sampling method.The findings of the study show that social media plays a significant role in influencing people's decisions on choice of tourist destinations and is also an important, cost effective, efficient and convenient marketing tool.Popularity of social media is also driven by its affordability and interactive nature.Findings also point out some challenges arising out of use of social media.The study concluded that social media plays a significant role in the tourism and hospitality sector.The study therefore recommended the adoption of social media for the purposes of creating positive perceptions on destinations to improve the pull power of destinations.The study also recommended the need to uplift the profile of social media in organisations through employment of appropriate staff to advance digital marketing on social media platforms.Another recommendation was to call for the enactment of policies to penalise detractors and culprits who peddle falsehoods and fake news on social media for ulterior motives.
Effect of Liberating Approach of Teaching on Students’ writing skills in English at Secondary School

Current The major purpose of this study was to compare the effectiveness of liberating approach of teaching with banking approach of teaching in the subject of English at secondary level in Pakistan. In order to develop the rational of the study, an experiment was devised to identify the effect of liberating approach of teaching on students’ achievement in the subject of English at secondary school level. Through this approach student creativity and mental power is stimulated and better used in academic and social context. The population of the study was included all the students of science and arts enrolled in 9th class in girls’ comprehensive higher secondary school of the Multan city. The researcher was selected two intact group sections of English medium science and both the sections have total 104 students. The study was Quasi Experimental with a Non-equivalent control group pre-test post-test design. One section was randomly selected an experimental group (X1) and the other was assigned to control group (X2).A pre-test and post-test were developed by the researcher, through carefully reviewing the methods of test development regarding quantifying students language skill, that is writing skills. A panel assessed the validity of both the test. The test had 50 marks for writing capacity (writing skills test).A pilot study was conducted to validate the instruments .The results also showed that treatment enhanced the achievement level of the experimental group in English. The researcher has confirmed that liberating approach is connected with learning techniques and strategies; and it is recommended that teacher of English should apply liberating approach to improve writing skills of the students in the classes. The findings revealed that liberating approach is more effective as compared to banking approach (traditional) of teaching. It is recommended that the teachers should apply liberating approach of teaching in the classes in order to improve writing skills of the students.
Shape Adaptor: A Learnable Resizing Module

We present a novel resizing module for neural networks: shape adaptor, a drop-in enhancement built on top of traditional resizing layers, such as pooling, bilinear sampling, and strided convolution. Whilst traditional resizing layers have fixed and deterministic reshaping factors, our module allows for a learnable reshaping factor. Our implementation enables shape adaptors to be trained end-to-end without any additional supervision, through which network architectures can be optimised for each individual task, in a fully automated way. We performed experiments across seven image classification datasets, and results show that by simply using a set of our shape adaptors instead of the original resizing layers, performance increases consistently over human-designed networks, across all datasets. Additionally, we show the effectiveness of shape adaptors on two other applications: network compression and transfer learning. The source code is available at: https://github.com/lorenmt/shape-adaptor.
OCCUPANCY BASED PATTERN MINING: CURRENT STATUS AND FUTURE DIRECTIONS

The main purpose of data mining and analytics is to find novel, potentially useful patterns that can be utilized in real-world applications to derive beneficial knowledge. In recent years, a new measure of pattern interestingness called occupancy of a pattern was introduced to ensure that each pattern found represents a large part of transactions where it appears. Main objective of this measure is to enhance the quality of a pattern. This article surveys recent studies on pattern mining and its applications based on occupancy. The goal of the paper is to provide both an introduction to occupancy based pattern mining (OPM), and a survey of recent advances and research opportunities. Moreover, main approaches and strategies to solve occupancy based pattern mining problems are also presented. The paper also presents challenges and research opportunities of using occupancy measure in other popular pattern mining problems.
CCS Library: How-To Videos: Overview

How-to videos and documents for Library resources including eBooks, databases, Luna, and using the catalog.
EXPERIMENTAL PROTOTYPE OF THE PRAGMATICALLY ORIENTED E-ASSESSMENT ALGORITHM FOR AUTOMATIC NATURAL LANGUAGE ANSWER GRADING

EXPERIMENTAL PROTOTYPE OF THE PRAGMATICALLY ORIENTED E-ASSESSMENT ALGORITHM FOR AUTOMATIC NATURAL LANGUAGE ANSWER GRADING
Cockroach Swarm Optimization Modifications and Application

In the chapter we focus on a cockroach swarm optimization (CSO) algorithm, which has the advantage of being easily implementable. We begin by giving a brief overview and the pseudo-code form of the CSO algorithm. Then, we present some modifications of CSO including inertia weight, stochastic constriction factor, hunger component, and various neighborhoods. Moreover, the purpose of this section is to demonstrate how the CSO algorithm can be adapted for solving combinatorial optimization problems. Therefore, we present an application of the CSO algorithm for the traveling salesman problem and its results. The final section derives useful conclusions.
Machine Learning for Patient Stratification and Classification Part 1: Data Preparation and Analysis

Machine Learning for Phenotyping is composed of three chapters and aims to introduce clinicians to machine learning (ML). It provides a guideline through the basic concepts underlying machine learning and the tools needed to easily implement it using the Python programming language and Jupyter notebook documents. It is divided into three main parts: part 1—data preparation and analysis; part 2—unsupervised learning for clustering, and part 3—supervised learning for classification.
Adventures with Oxides: Utilizing Commercial and Internal Reference Materials for Geological and Materials Science Samples

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Hex Triplet: #800000

Author(s): Reyes, Alexander | Abstract: This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.
QUALITY ASSURANCE FOR PROFESSIONAL TRAINING OF FUTURE SECONDARY EDUCATION MASTERS IN PHYSICAL CULTURE: EXPERIENCE OF THE REPUBLIC OF MOLDOVA

Basic approaches to quality assurance for professional training of future secondary education masters in physical culture in the Republic of Moldova have been studied on the example of professional training in State University of Physical Education and Sport (USEFS). Analysis of references and documents, methods of systematic analysis, comparison and juxtaposition allowed to reveal that “Psycho-pedagogy of physical education and sport” (USEFS) post-graduate educational program corresponds to native post-graduate program in “Secondary education. Physical culture”. “Psycho-pedagogy of physical education and sport” post-graduate educational program envisages a 2-year study and 120 ECTS credits. Subjects elected by master students are structured into fundamental and special modules. At the same time, these modules have different value; the special ones prevail. Curriculum envisages three modules for elective subjects. An integral component of educational process is writing master thesis and its defense. Formation of a future competitive master in psycho-pedagogy of physical education and sport is done due to internal system of quality assurance for professional training in the university and includes 5 major subdivisions: quality-matters council; department of quality management; internal audit commission; commission for pedagogical faculty quality assurance; a team for faculty’s departments’ quality assurance. Infrastructure of university’s quality functions based on the rules adopted by university’s Senate (the highest management body of a higher educational establishment).
Stellarium as An Interactive Multimedia to Enhance Students’ Understanding and Motivation in Learning Solar System

This research aims to determine the effectiveness of Stellarium as an Interactive Multimedia to students' understanding and motivation in learning the solar system.This study used a quasi-experimental design.The research was conduct in one of the private schools in Bandung which the number of students is 41.The Objective Test Item and Questionnaire were used as the research instrument.These instruments were given to experimental and control class as pretest and posttest.According to the analyses result, the value of Normalized gain in the experimental class and control class is 0.33 and 0.2.According to the Independent sample test result, the hypothesis in this research was accepted.The value of sig (2-tailed) is 0.019 with a significance value is 0.05.Thus, there is different of students" understanding using Stellarium in learning solar system; The students" motivation in learning solar system using Stellarium is categorized as adequately motivated.
Hunting Search Algorithm

The Hunting Search (HuS) method is an emerging metaheuristic optimization algorithm, which has been employed to deal with numerous challenging tasks during the last years. HuS algorithm is inspired by the underlying principles of the group hunting of animals such as lions, wolves, and dolphins. This numerical technique imitates the way of hunting process that takes place when hunters encircle the prey and gradually tighten the ring of siege until they catch the prey. Each member of the group corrects its position based on its own position and the position of other members for hunting similar to the optimum design process which seeks to find the optimum solution. In the present chapter, we will provide an introduction to the HuS algorithm. We will present the original version of the HuS algorithm in the pseudo-code form and its source code in Matlab, and in C++ programming language. Design examples are considered to demonstrate the efficiency of the algorithm presented. The results indicate that the proposed method is a powerful search and optimization technique. It yields better solutions compared to those obtained by some current algorithms when applied to continuous problems.
LibGuides: Education: Getting Started

This guide will get you started on your research in education. This blueprint guide can help you put together a useful subject guide.