Reviewerly/exHarmony huggingface dataset:
Retraction: Application Value and Applied Research of Diversified Teaching Based on Big Data Analysis in Oil Painting Teaching in Chinese Universities (J. Phys.: Conf. Ser. 1648 022020)

This article has been retracted by IOP Publishing following an allegation that raises concerns this article may have been created, manipulated, and/or sold by a commercial entity. In addition, IOP Publishing has seen no evidence that reliable peer review was conducted on this article, despite the clear standards expected of and communicated to conference organisers. The authors of the article have been given opportunity to present evidence that they were the original and genuine creators of the work, however at the time of publication of this notice, IOP Publishing has not received any response. IOP Publishing has analysed the article and agrees there are enough indicators to cause serious doubts over the legitimacy of the work and agree this article should be retracted. The authors are encouraged to contact IOP Publishing Limited if they have any comments on this retraction. Retraction published: 16 September 2022
Retraction: Huaer’s International Communication Strategy based on the Big Data under the Network Multimedia Propaganda (J. Phys.: Conf. Ser. 1648 022005)

This article has been retracted by IOP Publishing following an allegation that raises concerns this article may have been created, manipulated, and/or sold by a commercial entity. In addition, IOP Publishing has seen no evidence that reliable peer review was conducted on this article, despite the clear standards expected of and communicated to conference organisers. The authors of the article have been given opportunity to present evidence that they were the original and genuine creators of the work, however at the time of publication of this notice, IOP Publishing has not received any response. IOP Publishing has analysed the article and agrees there are enough indicators to cause serious doubts over the legitimacy of the work and agree this article should be retracted. The authors are encouraged to contact IOP Publishing Limited if they have any comments on this retraction. Retraction published: 16 September 2022
COMPARISON OF DEEP LEARNING ALEXNET AND SUPPORT VECTOR MACHINE TO CLASSIFY SEVERITY OF SICKLE CELL ANEMIA

Sickle cell anemia (SCA) is a serious hematological blood disorder, where affected patients are frequently hospitalized throughout a lifetime. Most of the patient's life span reduced, and some become addict based on the nature of strong analgesic that is taken by the concern patients, which they all have strong side effects. The existing method of severity classification for SCA patient is done manually through a microscope which is time-consuming, tedious, prone to error, and require a trained hematologist. The affected patient has many cell shapes that show important biomechanical characteristics of patient severity level. The main purpose of the study is to develop an automated severity level classification method of SCA patients by comparing deep learning AlexNet and Support Vector Machine (SVM) to enable present the percentage of each cell present in blood smear image. Hence, having an effective way of classifying the abnormalities present in the SCA disease based on the level of patient severity to give a better insight into managing the concerned patient's life. The study was performed with 182 SCA patients (over 11,000 single RBC images) with 14 classes of abnormalities and a class of normal cells to develop a shape factor quantification and general multiscale shape analysis to classify the patient based on severity level. As a result, it was found that the proposed framework can detect 85.4% abnormalities in SCA patient blood smear in automated manner when compared with Support Vector Machine (SVM) method with 71.9%. Hence, the system classifies the severity of SCA patient automatically and reduce the time and eye stress with performance AlexNet model performance of 95.1% accuracy, 99.1% specificity, and 98.5% precision value.
PROB-SLAM: Real-time Visual SLAM Based on Probabilistic Graph Optimization

Traditional SLAM algorithms are typically based on artificial features, which lack high-level information. By introducing semantic information, SLAM can own higher stability and robustness rather than purely hand-crafted features. However, the high uncertainty of semantic detection networks prohibits the practical functionality of high-level information. To solve the uncertainty property introduced by semantics, this paper proposed a novel probability map based on the Gaussian distribution assumption. This map transforms the semantic binary object detection into probability results, which help establish a probabilistic data association between artificial features and semantic info. Through our algorithm, the higher confidence will be given higher weights in each update step while the edge of the detection area will be endowed with lower confidence. Then the uncertainty is undermined and has less effect on nonlinear optimization. The experiments are carried out in the TUM RGBD dataset, results show that our system improves ORB-SLAM2 by about 15% in indoor environments' errors. We have demonstrated that the method can be successfully applied to environments containing dynamic objects.
Mobilex: a generic framework for cross-platform mobile development based on web language

Several mobile development frameworks allow developers to program a single code to run on different types of devices and operating systems. However, the application code is dependent on the chosen framework, making it difficult to reuse it when there is a need to migrate to other frameworks. This paper proposes a generic framework for cross-platform mobile development, which uses web technologies (HTML, CSS, and JavaScript) as a basis for application development. The use of this technology to define the application and its automatic translation to a platform-specific language makes it easier to produce and maintain the application on multiple platforms. This paper discusses the proposed approach and shows, through case studies, that it allows flexibility in the choice of cross-platform development framework, not being necessary to change the code already developed in case of change in the development platform. Video presentation: https://youtu.be/ZS152tXUqBQ
Being Real About Teaching Virtual: Comparing Academic and Industry Views on Technology Integration and Skill Development

The purpose of this study was to examine the benefits and challenges of the decision to adopt new 3D virtual technologies from the perspective of faculty who teach in apparel programs and to compare faculty perspectives with those of industry professionals who are in a position to hire apparel program graduates. Data were collected with faculty via an online questionnaire and through virtual interviews with 15 industry professionals who work at apparel and retail companies. Findings of the study illustrate that while there are areas of overlap in terms of faculty and industry perspectives, especially the need for students to learn 3D and virtual technologies and the relatively high costs involved in doing so, there are also some differences, including the kinds of skills that should be developed. Further study can help to better align the goals of industry for hiring new graduates with the resources available to apparel programs to support such technologies. <br>
Framework for the development of computational solutions for the support of requirements engineering with a focus on data protection

Technological growth has allowed the large-scale processing of personal data, sometimes treated for purposes not previously consented with their subjects or without the required protection. Privacy is a crucial topic that has become popular with the entry into force of regulations such as GDPR and LGPD. Research shows that adhering to these regulations is not trivial for companies that develop solutions that treat personal data. This scenario is worsened by the lack of knowledge of software development teams regarding data protection regulations. In this context, the present work aims to support teams in building software requirements adhering to data protection regulations through a workflow-based framework. The workflow analyzes the requirement from various points of view related to data protection, indicating points of improvement for developing the software in question. We developed a practical example to demonstrate the framework’s applicability, analyzing a software requirement. The obtained results are promising.
Children and Young People’s Involvement in Designing Applied Games: Scoping Review (Preprint)

<sec> <title>BACKGROUND</title> User involvement is widely accepted as key for designing effective applied games for health. This especially holds true for children and young people as target audiences, whose abilities, needs, and preferences can diverge substantially from those of adult designers and players. Nevertheless, there is little shared knowledge about how concretely children and young people have been involved in the design of applied games, let alone consensus guidance on how to do so effectively. </sec> <sec> <title>OBJECTIVE</title> The aim of this scoping review was to describe which user involvement methods have been used in the design of applied games with children and young people, how these methods were implemented, and in what roles children and young people were involved as well as what factors affected their involvement. </sec> <sec> <title>METHODS</title> We conducted a systematic literature search and selection across the ACM Digital Library, IEEE Xplore, Scopus, and Web of Science databases using State of the Art through Systematic Review software for screening, selection, and data extraction. We then conducted a qualitative content analysis on the extracted data using NVivo. </sec> <sec> <title>RESULTS</title> We retrieved 1085 records, of which 47 (4.33%) met the eligibility criteria. The chief involvement methods were participatory design (20/47, 43%) and co-design (16/47, 37%), spanning a wide range of 45 concrete activities with paper prototyping, group discussions, and playtesting being the most frequent. In only half of the studies (24/47, 51%), children and young people participated as true design partners. Our qualitative content analysis suggested 5 factors that affect their successful involvement: comprehension, cohesion, confidence, accessibility, and time constraints. </sec> <sec> <title>CONCLUSIONS</title> Co-design, participatory design, and similar high-level labels that are currently used in the field gloss over very uneven degrees of participation in design and a wide variety of implementations that greatly affect actual user involvement. This field would benefit from more careful consideration and documentation of the reason of user involvement. Future research should explore concrete activities and configurations that can address the common challenges of involving children and young people, such as comprehension, cohesion, confidence, and accessibility. </sec>
ARCHIVING AND LANGUAGE DOCUMENTATION

This article is derived from a conference at the ABRALIN ao vivo, held online, in 2020. The goal is to discuss the benefits and challenges associated with archiving in language documentation considering our accumulated knowledge as scholars who are deeply involved in administering, contributing to, and drawing on language archives, with an emphasis on the indigenous languages of Latin America. We focus in particular on the relevance of language archiving in Brazil, and its significance for scholars, community members, and other stakeholders.
Getting to Know Your Customer

This chapter covers Agile, Waterfall, and hybrid product management practices based on a customer-centric approach to IT delivery. It builds on the knowledge of business objectives to focus on customer needs. It explains the concept of a persona type and provides tools and templates to identify the customer, empathize with the customer’s problem, and define the product while “working backward” from customer needs.
Practicing Cooperative Learning Model Using Picture Cube and Story Marker to Improve Writing Skills

Cooperative learning provides various activities in the form of individual and group works in teaching language skills. This research aims to improve the writing skills ability using cooperative learning model. This study was action research. The research was conducted in one cycle following the cyclical action research model consisting of planning, acting, observing, and reflecting. The subjects of this research were 20 students in Class 8D. In this research, there was two types of data, it is qualitative and quantitative data. The qualitative data are analyzed following three stages of qualitative data analysis, namely data collection, data condensation, data display, conclusion drawing, and final reporting. Meanwhile, the quantitative data cover studentsâ€™ writing achievement collected using writing tests. The findings of this research show that the studentsâ€™ writing skills are improved. They mastered key vocabulary and grammatical knowledge to compose sentences. The students kept on using writing strategies through cooperative learning model to understand a given text. The teaching and learning activities were interesting. Media used are Picture Cube and Story Marker to support cooperative learning activities. It is elaborated in discussion part of this article.
Legal and regulatory frameworks

The e-commerce legislation necessary to support the development of e-commerce in the country has been adopted. This legislation includes, among others, the Kenya Information and Communication Act, Rev. 2009 (amended in 2013); the Consumer Protection Act, 2012; the Data Protection Act, 2019; and the Computer Misuse and Cybercrimes Act, 2018. Nonetheless, the Consumer Protection Act, 2012 needs to be amended to address several gaps relating to e commerce. There is also a need for increased public sensitization on these laws and sensitization of the duty bearers for increased compliance. There is also a need for improved enforcement of these regulations to stem the cases of fraud (such as misleading advertisement, payment fraud and non-delivery of goods), cybercrime and other issues hindering the growth of e-commerce.
Two-Variable Regression Models

An R Companion for The Fundamentals of Social Research offers students the opportunity to delve into the world of R using real data sets and statistical analysis techniques directly from Paul M. Kellstedt, Guy D. Whitten, and Steven A. Tuch's new textbook. Workbook sections parallel chapters in the main text, giving students a chance to apply the lessons and techniques learned in each chapter in a statistical software setting. Detailed chapters teach students to reproduce results presented in the textbook, allowing them to become comfortable performing statistical analyses for evaluating causal claims through repeated practice. Step-by-step instructions for using R are provided, along with command lines and screenshots to demonstrate proper use of the software. Instructions for producing the figures and tables in the main text are integrated throughout the workbook. End-of-chapter exercises encourage students to formulate and evaluate their own hypotheses.
The Scientific Study of Society

An R Companion for The Fundamentals of Social Research offers students the opportunity to delve into the world of R using real data sets and statistical analysis techniques directly from Paul M. Kellstedt, Guy D. Whitten, and Steven A. Tuch's new textbook. Workbook sections parallel chapters in the main text, giving students a chance to apply the lessons and techniques learned in each chapter in a statistical software setting. Detailed chapters teach students to reproduce results presented in the textbook, allowing them to become comfortable performing statistical analyses for evaluating causal claims through repeated practice. Step-by-step instructions for using R are provided, along with command lines and screenshots to demonstrate proper use of the software. Instructions for producing the figures and tables in the main text are integrated throughout the workbook. End-of-chapter exercises encourage students to formulate and evaluate their own hypotheses.
Quantum-limited absorption estimation with ring resonators

Coherent-state probes in appropriately designed all-pass ring resonators outperform any quantum probe single-pass absorption estimation strategy, including those using Fock or bright squeezed states.
New Zealand: Curbing Hate Speech, But Leaving Platforms to Self-Regulate

In March 2019, a terrorist killed 51 people in Christchurch mosque attacks, livestreaming his actions on Facebook. The attacks lead the country into a critical juncture: the New Zealand government was expected to abandon its relaxed attitude to platform regulation, and to implement strict rules to govern them. While the government has taken some measures to curb platforms’ behaviour, it has largely followed its neoliberal path in regulation, mostly leaving platforms to govern themselves. While regulating platform corporations is taxing, New Zealand’s attitude is somewhat surprising. A recent inquiry into mosque attacks, for example, concluded that Google-owned YouTube was an “inspiration” to the terrorist. It has been claimed that platform companies’ algorithms can amplify extreme content, yet, New Zealand’s new Algorithm Charter fails to mention them.
ADE 2022 Day 1: Background and Fieldwork v2

ADE 2022 description of work to be done on Day 1 of the practical work
Knowing Your Clients Using Monads

Remember that you have been commissioned to build a Time Machine Store. Apart from a beautiful design and an intuitive user experience, a good web store should adapt itself to the customers’ likes and needs by keeping track of clients and analyzing their behavior. With that information, better campaigns, such as discounts or targeted ads, can be developed, increasing sales. For these tasks, many data mining algorithms have been developed. In this chapter, you will focus on clustering algorithms, which try to find groups of related clients. You will use a specific implementation of clustering, called K-means, using Haskell.
Learning distant cause and effect using only local and immediate credit assignment

We present a recurrent neural network memory that uses sparse coding to create a combinatoric encoding of sequential inputs. Using several examples, we show that the network can associate distant causes and effects in a discrete stochastic process, predict partially-observable higher-order sequences, and enable a DQN agent to navigate a maze by giving it memory. The network uses only biologically-plausible, local and immediate credit assignment. Memory requirements are typically one order of magnitude less than existing LSTM, GRU and autoregressive feed-forward sequence learning models. The most significant limitation of the memory is generalization to unseen input sequences. We explore this limitation by measuring next-word prediction perplexity on the Penn Treebank dataset.
Study of Potential Utilization of Recycling Ablution Used Water, Case Study at Ulul Albaab Mosque, Universitas Pasundan, Bandung, Indonesia

The role of water in daily life, including activities in the mosque is very significant. The existence of the Ulul Albaab Mosque which is always busy with various congregation activities and activities carried out by students and the campus community affects the need for clean water. So far, the ablution used water at the Ulul Albaab Mosque has been dumped into the sewers. Measuring the quantity of water to determine the volume of ablution used water at the time of obligatory prayer is the first step to assessing its potential utilization. The number of congregation who perform ablution is directly proportional to the number of congregation of the Ulul Albaab Mosque. The average congregation of the mosque is 857 people/day and the average number who perform ablution is 778 people/day. The results showed that the volume of water used for ablution was 3.9 liters/person with an average time required for ablution of around 64 seconds. The use of recycling ablution water can be used for non-consumption needs.
Overcoming Virtual Training Challenges to Promote the Adoption of Cloud Solutions

Abstract Cloud solutions play an essential role in digital transformation in the oil and gas industry. Training is key to promote cloud solutions and accelerate digital transformation. Unlike legacy computer-based software, agile development, which continuously releases new features of cloud solutions, makes the learning process more challenging because of the necessarily fast-paced adoption of the knowledge. Another challenge was that we had to virtually deliver the training sessions because of the pandemic during 2020 and 2021, which made the interaction with students very difficult without face-to-face contact. To be ready for the virtual training challenges, a self-guided quick-learning page was created and leveraged to bridge the gap between the continuous release of new features in cloud solutions and the fast-paced knowledge adoption. Training materials, including the self-training page, were updated once every quarter to reflect the new features in the cloud solutions. Unlike traditional software, after each training, the web-based training environment (tenant) was occupied by many training projects created by students, which made it difficult to be used by the new group of students. To solve this issue, a new procedure was developed to efficiently reset the tenant to ensure a smooth and data-secured training. As the training requests grew exponentially, more than 35 training tenants were created to meet the high demand and frequency of training from different customers across the world. The self-guided quick-training page has more than 17,454 visits and 600 unique users, with positive feedback from students. In 2021, more than 630 users from 40 countries were successfully trained. This is a two-fold increase from 2020 and a five-fold increase from 2019. In this paper, we provide new insight to successfully deliver virtual training and promote the adoption of cloud solutions in the digital transformation of the exploration and production industry.
Cephalic and Facial Indices among Adult Females of Kurseong

The present cross-sectional study in Kurseong of Darjeeling district, West Bengal, India was conducted among adult Nepali speaking Hindu females, aged 18 to 46 years. The aim of the study was to find out the cephalic and facial index of adult Nepali females. All measurements were taken by using standard techniques. The mean age was 35.56 (SD 8.56) years. It was observed that Mesocephal form was the dominant head type and Mesoprosop was the dominant face type among the studied population.
Image Processing Technique in Measuring Underwater Target's Properties

Due to light refraction effect, the need to design a proper technique for underwater scene is a critical task. The problem began to be appeared at deeper levels of water and hence, one cannot distinguish nor observe the properties for underwater objects. The properties may include dimensions, color, texture, etc. So, the current paper involves such situation through designing a system prepared for this purpose with the use of two types of water; an ordinary type with an addition of alum and distilled water. The presented work aims to measure object’s properties of three different objects immersed inside such system. Results show a complete match between the actual and estimated values for the relationship between the two used laser spots distance-water depth variation for the two used sources of water. In addition to that, a special convergence appeared clearly upon the actual and estimated values in detecting underwater object's properties especially at water depth that exceed one meter.