Reviewerly/exHarmony huggingface dataset:
The Proposed Critical Factors to Improve the Performance of Scrum Teams

Scrum is one of the most popular and widely practiced agile software development methodologies. Scrum team consists of a Scrum Master, Product Owner, and developers. While using Scrum, several factors have been reported in the existing studies to improve or lower the performance of a Scrum team such as managing the priority of the product backlog items, role of an efficient product owner, cost and time to perform integration tests, accurate estimation of story points and code quality. This paper aims to determine critical factors those impact the most over the performance of the Scrum teams using a survey and systematic literature review. Furtherly, a model is proposed presenting the impact of critical factors to enhance the performance of Scrum teams to increase efficiency and work perfection, organizing and managing product backlogs, clarity in goals, execution of sprints in an estimated duration and increase productivity of product owner. The identified critical factors are validated using a survey and the results are found encouraging.
Introduction to WebXR

course Introduction to WebXR: SIGGRAPH 2021 course Share on SIGGRAPH '21: ACM SIGGRAPH 2021 CoursesAugust 2021 Article No.: 3Pages 1–89https://doi.org/10.1145/3450508.3464557Online:21 July 2021Publication History 0citation127DownloadsMetricsTotal Citations0Total Downloads127Last 12 Months127Last 6 weeks11 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Information Management in Project Management

The authors start by presenting a disciplinary positioning regarding the information science (IS) that is being developed, investigated, and taught at the University of Porto, Portugal and rigorously spelling out the cross-cutting approach to information management (IM), which is also shared with other social sciences and technology-oriented disciplines. From this point, it is presented a short overview and a literature review about the nature of project management (PM) to emphasize the need for an effective and fully assumed approach between IM and PM. It is observed that for PM specialists, info-communicational flows are important, and they seek to manage them intuitively, but without feeling compelled to draw on the know-how of the IS and IM specialists. However, the opposite is true, that is, there are in course some interesting adaptations of PM procedures, applied to informational projects, as it is shown in the last part of this chapter.
Microsoft Kinect Sensor Used to Capture Data for Robotics Applications: A Recent Study

The process of capturing digital images has greatly evolved since the initial appearance of photography in general. In recent years, this evolution has been greatly accelerated by the development of high resolution and specialized digital capture sensors which, in turn, has opened the door for research to develop new products and algorithms allowing imaging to be used as input for controlling different other devices or robots. Still, for there to be a real mapping between a digital image and physical word a lot of research has been done in the field of algorithms and sensors, which have lately resulted in the emergence of affordable and specialized devices on the market like Microsoft Kinect or Motion Leap. Initially, the Microsoft Kinect device was exclusively used for the gaming industry, but later captured the attention of the research community, who quickly noticed that the sensor could be used as a very affordable alternative in the three-dimensional mapping process of space. Soon, an SDK was developed by PrimeSense (OpenNI), which allowed the sensor to be used for any other purpose, not just in the field of games. One of these opportunities is the use of the sensor in the field of image analysis for which a product to capture the movement of a human was developed and is presented in this paper along with a proposal to use the capture mechanism to command and control an industrial robotic arm. The presented issues can be used with minimal adaptations and for more advanced Kinect sensor variations that are already underway or will be carried out in the future for similar applications.
A GNN-based Multi-task Learning Framework for Personalized Video Search

Watching online videos has become more and more popular and users tend to watch videos based on their personal tastes and preferences. Providing a customized ranking list to maximize the user's satisfaction has become increasingly important for online video platforms. Existing personalized search methods (PSMs) train their models with user feedback information (e.g. clicks). However, we identified that such feedback signals may indicate attractiveness but not necessarily indicate relevance in video search. Besides, the click data and user historical information are usually too sparse to train a good PSM, which is different from the conventional Web search containing users' rich historical information. To address these concerns, in this paper we propose a multi-task graph neural network architecture for personalized video search (MGNN-PVS) that can jointly model user's click behaviour and the relevance between queries and videos. To relieve the sparsity problem and learn better representation for users, queries and videos, we develop an efficient and novel GNN architecture based on neighborhood sampling and hierarchical aggregation strategy by leveraging their different hops of neighbors in the user-query and query-document click graph. Extensive experiments on a major commercial video search engine show that our model significantly outperforms state-of-the-art PSMs, which illustrates the effectiveness of our proposed framework.
A Distributed and Privacy-Preserving Random Forest Evaluation Scheme with Fine Grained Access Control

Random forest is a simple and effective model for ensemble learning with wide potential applications. Implementation of random forest evaluations while preserving privacy for the source data is demanding but also challenging. In this paper, we propose a practical and fault-tolerant privacy-preserving random forest evaluation scheme based on asymmetric encryption. The user can use asymmetric encryption to encrypt the data outsourced to the cloud platform and specify who can access the final evaluation results. After receiving the encrypted inputs from the user, the cloud platform evaluates via a random forest model and outputs the aggregated results where only the designated recipient can decrypt them. Threat analyses prove that the proposed scheme achieves the desirable security properties, such as correctness, confidentiality and robustness. Moreover, efficiency analyses demonstrate that the scheme is practical for real-world applications.
Seismic event detection in suburban Chicago using a single broadband seismic station

Earth and Space Science Open Archive PosterOpen AccessYou are viewing the latest version by default [v1]Seismic event detection in suburban Chicago using a single broadband seismic stationAuthorsAnn MariamThomasiDHaoZhangSuzanvan der LeeSee all authors Ann Mariam ThomasiDCorresponding Author• Submitting AuthorNorthwestern UniversityiDhttps://orcid.org/0000-0001-6271-1738view email addressThe email was not providedcopy email addressHao ZhangNorthwestern Universityview email addressThe email was not providedcopy email addressSuzan van der LeeNorthwestern Universityview email addressThe email was not providedcopy email address
Improving Students’ Writing Skill in Writing Narrative Text Through Picture And Picture Method

One of the important materials in reading skills is narrative text. The narrative text is taught since the 8th grade of Junior High School and is a mandatory material until it is included in the National Examination (UN) grid, college entrance exams, and TOEFL. The narrative text is a type of English text that aims to tell a story that has a series of connected chronological events. It is the main part of English text taught in Junior High School. Unfortunately, researchers still found many students who did not master narrative texts, especially in grade 8 of SMP Ibrahimy 1 Sukorejo. The picture and picture model is one of the learning models that can improve students' writing skills in narrative texts. The Picture and Picture model has the same principle and way of working as the method of learning to compose pictures. Students are equally asked to arrange pictures that have been prepared sequentially and systematically. Systematic and sequential according to the reasoning and logical strength of students. This research used the classroom action research method and was conducted in 2 cycles through four stages, namely planning, implementation, observation, and reflection. Data collection techniques used were observation, questionnaires, and tests. The finding of this research showed that picture and picture models could improve students’ writing skills in writing narrative text.
Secured Access and Security Issues of Maintenance for Cloud Database

Users are using the cloud database services for storing there important data in order to utilized cloud services. Data confidentiality remains one of the main concerns and the major barrier to the development of cloud services. But at the same time users also think about “whether there data is in secured hands and how it is protected from the outside world?” In order to make sure users that there data is in safe hands, cloud database are using more secured mechanism for accessing the cloud database. In order to achieve the goal of security we are using AES and honey encryption (HE) algorithm for strong authorization. Before authorization we need to have authentication of the users. We are using keystroke dynamics as a biometrics authentication and second one as color code authentication. Cloud databases should also be properly maintained from security point of view. For the different levels of the cloud database we have find out the security issues which provide help in maintenance of cloud database. By implementing these issues the security of the cloud database will be more increased.
Sistem Informasi Penjualan Ayam Potong Berbasis Android Pada UD. Abdul Aziz

Sales of chicken pieces At “UD. Abdul Aziz" is one of the business entities engaged in sales or referred to as self-employed, sales serving customers, especially in the service sector, still use the manual method. This goods sales information system is made using PHP, HTML and MYSQL. This program allows admins to input data, edit reports, delete data, search transactions. The data inputted are chicken data, chicken type data and chicken sales data. This chicken sales information system can be a solution that can be used to facilitate sales in processing chicken sales data, making it easier, faster and more efficient.
Organizing experiential activities in the topic “Growing plants with hydroponic solutions” in Chemistry Grade 11 to develop problem-solving capacity for students

The born of the general education program stipulates that experience activities (primary level) and experiential and career-oriented activities (junior high school and high school levels) are both required educational activities carried out from grade 1 to grade 12 to assist students to develop competencies, skills, beliefs, ethics in order to promote creative potential and adaptability to life, environment, and profession future career [1]. Within the scope of this article, we briefly study the theoretical basis of experiential activity. Therefore, developing the topic of experiential activity "Growing plants with a hydroponic solution" in the Chemistry Grade 11 (2018 program) in order to develop problem-solving capacity for students. Experimental reveal that experiential and career-oriented activities assist students to develop their problem-solving abilities, contributing to improving the quality of education and training, which is appropriate in the period of educational reform nowadays.
AN ENHANCED INTERACTION AND FILTERING WIDGET

In information visualization, interaction mechanisms are an essential factor to the success of visualization.They should be easy to use and useful for filtering, exploring, and analyzing the data visualized.Usually, direct manipulation on the visualizations is the most important aspect that researches consider.However, users still tend to use controls (widgets) for some interaction, especially, when manipulating (e.g., filtering) the data.During our work with users on the visual representation of safety analysis results, we found limitations in the interaction capabilities of sliders.In order to overcome these limitations, we introduce our Range-Selection-and-Filtering RSF slider, which enables users to work more efficiently when selecting relevant data from large data sets compared to conventional slider designs by enhancing the ease of use and increasing its usefulness.Additionally, we applied this slider to different application domains and evaluated it.
Execution Assessment of Machine Learning Algorithms for Spam Profile Detection on Instagram

Witheverypassingsecondsocialnetworkcommunityisgrowingrapidly,becauseofthat,attackershaveshownkeeninterestinthesekindsofplatformsandwanttodistributemischievouscontentsontheseplatforms.Withthefocus on introducing new set of characteristics and features forcounteractivemeasures,agreatdealofstudieshasresearchedthe possibility of lessening the malicious activities on social medianetworks. This research was to highlight features for identifyingspammers on Instagram and additional features were presentedto improve the performance of different machine learning algorithms. Performance of different machine learning algorithmsnamely, Multilayer Perceptron (MLP), Random Forest (RF), K-Nearest Neighbor (KNN) and Support Vector Machine (SVM)were evaluated on machine learning tools named, RapidMinerand WEKA. The results from this research tells us that RandomForest (RF) outperformed all other selected machine learningalgorithmsonbothselectedmachinelearningtools.OverallRandom Forest (RF) provided best results on RapidMiner. Theseresultsareusefulfortheresearcherswhoarekeentobuildmachine learning models to find out the spamming activities onsocialnetworkcommunities.
Prevalence of Malaria among Patients Attending Primary Health Care Clinic Garaku, Nasarawa State, North Central Region of Nigeria

The aim of this study was to determine the prevalence of malaria parasite infection (MPI) among patients attending Primary Health Care clinic (PHC) at Garaku, Kokona Local Government Area of Nasarawa State North Central Nigeria. A formal consent was issued by the Nasarawa State Hospital management Board to conduct the study. A studypopulation size of150 consenting, apparently healthy, males and females who had attended the Primary Health Care clinic situated at Garaku, Kokona Local, Government of Nasarawa State, for medical treatment, were recruited for the study. The study took place between the month of May 2019 and September 2019. The socio-demographic features of each participant were verbally obtained, and included sex, age, occupational and educational statuses. The gold standard tool (microscopy) was relied upon to determine the prevalence of malaria infection among the subjects. Blood samples collected from patients were Giemsa stained and microscopically examined for malaria parasites. Analysis of the samples revealed malaria prevalence of 53.3 %among the sampled population. Further analysis onmalaria prevalence with respect to factors such as age, educational and occupational status revealed that malaria infection was more prevalent among the civil servants (75%), followed by the elderly (71.4%), and followed by the educated (73.3%) in the population. In conclusion, the study established that women, civil servants, the elderly, and the least educated were more vulnerable to malaria infection within the study location
On Cryptographic Parameters of Permutation Polynomials of the form &lt;i&gt;x&lt;sup&gt;r&lt;/sup&gt;h&lt;/i&gt;(&lt;i&gt;x&lt;/i&gt;&lt;sup&gt;(2&lt;i&gt;&lt;sup&gt;n&lt;/sup&gt;&lt;/i&gt;-1)/&lt;i&gt;d&lt;/i&gt;&lt;/sup&gt;)

The differential uniformity, the boomerang uniformity, and the extended Walsh spectrum etc are important parameters to evaluate the security of S (substitution)-box. In this paper, we introduce efficient formulas to compute these cryptographic parameters of permutation polynomials of the form xrh(x(2n-1)/d) over a finite field of q=2n elements, where r is a positive integer and d is a positive divisor of 2n-1. The computational cost of those formulas is proportional to d. We investigate differentially 4-uniform permutation polynomials of the form xrh(x(2n-1)/3) and compute the boomerang spectrum and the extended Walsh spectrum of them using the suggested formulas when 6≤n≤12 is even, where d=3 is the smallest nontrivial d for even n. We also investigate the differential uniformity of some permutation polynomials introduced in some recent papers for the case d=2n/2+1.
Anomalies

The Standard Model of particle physics is an amazingly successful theory describing the fundamental particles and forces of nature. This text, written for a two-semester graduate course on the Standard Model, develops a practical understanding of the theoretical concepts it's built upon, to prepare students to enter research. The author takes a historical approach to demonstrate to students the process of discovery which is often overlooked in other textbooks, presenting quantum field theory and symmetries as the necessary tools for describing and understanding the Standard Model. He develops these tools using a basic understanding of quantum mechanics and classical field theory, such as Maxwell's electrodynamics, before discussing the important role that Noether's theorem and conserved charges play in the theory. Worked examples feature throughout the text, while homework exercises are included for the first five parts, with solutions available online for instructors. Inspired by the author's own teaching experience, suggestions for independent research topics have been provided for the second-half of the course, which students can then present to the rest of the class.
Assessing students' natural science capacity through the theme "Substances and variation of substances”

The Natural Science Educational Program is implemented from 2021 - 2022, the secondary schools where are allowed to use one of the textbook sets for this program. The assessment is aimed at evaluating the capacity and capacity development of students, in which natural science competence is a specific ability of the subject. However, the teachers still have many difficulties in assessing students' abilities. In this study, we have proposed and described in detail the levels of assessment of natural science competence through a specific topic. At the same time, we have suggested a competency assessment process for teachers to implement. The results of this study aim to help secondary school teachers do this work effectively, meeting the requirements of the General Education Program 2018.
Sharing Dependency Parsers between Similar Languages

A summary is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
Performance Tips

Many times data visualization requires lots of resources to run. For instance, consider the features that a common chart includes: animations, a live data feed updating at runtime, a chart with thousands of records or a few charts placed on a single page, and so on.
Mining Frequent Itemsets over Uncertain Database using Matrix

In the area of data mining for finding frequent itemset from huge database, there exist a lot of algorithms, out of all Apriori algorithm is the base of all algorithms. In Uapriori algorithm each items existential probability is examined with a given support count, if it is greater or equal then these items are known as frequent items, otherwise these are known as infrequent itemsets. In this paper matrix technology has been introduced over Uapriori algorithm which reduces execution time and computational complexity for finding frequent itemset from uncertain transactional database. In the modern era, volume of data is increasing exponentially and highly optimized algorithm is needed for processing such a large amount of data in less time. The proposed algorithm can be used in the field of data mining for retrieving frequent itemset from a large volume of database by taking very less computation complexity.
LAISSEZ-FAIRE LEADERSHIP POSITIVELY IMPACTS ORGANISATIONAL COMMITMENT IN HEALTHCARE CENTRES IN QATAR

Leadership engenders an essential element for organisations to develop business strategies and achieve their goals. This research aims to examine the impact of laissez-faire leadership style on organisational commitment (OCOM) in health care centers in Qatar. The researcher adopted a quantitative approach, using a self-administered questionnaire to collect the primary data. The sample consisted of 218 leaders and supervisors from five healthcare centers in Qatar selected employing non-random sampling. The study indicated a significant positive relationship existed between laissez-faire leadership and OCOM. Moreover, leadership behavior significantly impacted OCOM behaviors. but in different degrees: continuance commitment and normative commitment to a higher extent, and affective commitment less so. Also, the results showed the percentage to which Laissez-Faire leadership style was practiced, in the sample, to be high.
Scientific and methodological bases of professional training of future chemistry teachers

The purpose of this article is to study the knowledge of teachers in the field of chemical and technological science. Using new learning modules, new principles of computational chemistry for chemistry teachers are explored.
Retraction: Detection of Leukemia Using Machine Learning Algorithms (J. Phys.: Conf. Ser. 1916 012220)

This article (and all articles in the proceedings volume relating to the same conference) has been retracted by IOP Publishing following an extensive investigation in line with the COPE guidelines. This investigation has uncovered evidence of systematic manipulation of the publication process and considerable citation manipulation. IOP Publishing respectfully requests that readers consider all work within this volume potentially unreliable, as the volume has not been through a credible peer review process. IOP Publishing regrets that our usual quality checks did not identify these issues before publication, and have since put additional measures in place to try to prevent these issues from reoccurring. IOP Publishing wishes to credit anonymous whistleblowers and the Problematic Paper Screener [1] for bringing some of the above issues to our attention, prompting us to investigate further. [1] Cabanac G, Labbé C and Magazinov A 2021 arXiv: 2107.06751v1 Retraction published: 23 February 2022
Cognitive essence of the mathematical picture of the world and the problem of understanding mathematical knowledge

The mathematical picture of the world has general ideas about mathematical objects and their characteristic properties. It is based on some system of initial fundamental basic mathematical concepts and mathematical theories. If the structure of the mathematical picture of the world does not focus on the process of obtaining knowledge, then the philosophy of mathematical education focuses on ways of understanding and substantiating mathematics in terms of the truth of mathematical statements, as well as on ideas about the effectiveness of mathematics in applications.