Reviewerly/exHarmony huggingface dataset:
3D Visualisations Should Not be Displayed Alone - Encouraging a Need for Multivocality in Visualisation

We believe that 3D visualisations should not be used alone; by coincidentally displaying alternative views the user can gain the best understanding of all situations. The different presentations signify manifold meanings and afford different tasks. Natural 3D worlds implicitly tell many stories. For instance, walking into a living room, seeing the TV, types of magazines, pictures on the wall, tells us much about the occupiers: their occupation, standards of living, taste in design, whether they have kids, and so on. How can we similarly create rich and diverse 3D visualisation presentations? How can we create visualisations that allow people to understand different stories from the data? In a multivariate 2D visualisation a developer may coordinate and link many views together to provide exploratory visualisation functionality. But how can this be achieved in 3D and in immersive visualisations? Different visualisation types, each have specific uses, and each has the potential to tell or evoke a different story. Through several use-cases, we discuss challenges of 3D visualisation, and present our argument for concurrent and coordinated visualisations of alternative styles, and encourage developers to consider using alternative representations with any 3D view, even if that view is displayed in a virtual, augmented or mixed reality setup.
Multi-point Fundraising and Distribution via Blockchain

Trust and transparency are significant facets that are much esteemed by charitable organizations in achieving their mission and encouraging donations from the public.However, after many high-profile scandals, the faith in charities is questionable, heralding the need for an increased level of transparency among such organizations.Fortunately, leveraging Blockchain technology in charities' systems could help to rebuild the integrity of these organizations.This study aims to raise the level of integrity showcased by charities by creating a multi-point fundraising approach using smart contracts.The proposed system offers a transparent fundraising platform through its integration of charity organization evaluators.Various steps were deployed to satisfy the intended target.Firstly, the study investigated the potentials of Blockchain in improving the level of transparency.Secondly, a probing process was undertaken to choose a suitable platform as a server-side in the system.This process involved garnering salient features in Blockchain platforms based on the proposed system requirements.After the probing process, a Decision Support System (DSS) was utilized to investigate the most suitable Blockchain platform.Results garnered proved that the Ethereum platform is best for the proposed system.
Haar-features training parameters analysis in boosting based machine learning for improved face detection

There is very strong motivating factor for doing research in the field face biometrics for the purpose of authentic access to various resources.In the prevalent situation of pandemic COVID-19, remote logging as well as contactless authentication systems have emerged out to be of great importance.There has been a tremendous rise in usage of video cameras and surveillance systems, thereby giving more impetus to research in the domain of face detection and facial image processing systems which is mostly machine learning based.Features are an important constituent used in the framework of classification task.
Expectancy-Based Decision Schemes: Sidesteps Toward Applications

Much of the expectancy value/decision theory research has focused on the descriptive or predictive adequacy of the models. This chapter examines studies that have used the models as means to other ends. It begins with a discussion on probability with primary emphasis on subjective probabilities because they are more likely to be used in personal and public decisions than objective probabilities—a short background to provide a bit of perspective and then some examples of current work. Next, the chapter provides information on utility. It describes Subjective Expected Utility (SEU), that is left until last because, conceptually if not actually, it presupposes the previous two sections. An example of the application of SEU is in the area of family planning. This is an example of a complexly multiattributed, risky decision and, as such, is attractive for application of Multiattribute Utility Theory/SEU.
Enabling Location k-Anonymity in Social Networks

Location-based services (LBSs) are services provided on the basis of the position of users. There are different types of LBSs and different possible scenarios, but, in any case, serious privacy threats arise. Indeed, localization information can be sensitive per se, and because it might play as a quasi-identifier allowing the break of anonymity in the case of services delivered to anonymous customers. Moreover, the content of LBS queries might include a lot of information that exposes the user to privacy leaks, if the queries can be linked to the identity of the user. All the above privacy concerns assume a concrete relevance whenever we consider the case of honest-but-curious providers, possibly exploiting background information and colluding with external parties. The problem is even more serious when the social network provider is also the provider of LBSs (as it happens for many real-life social networks). In this chapter, we analyze this and other problems by focusing on the problem of protecting location data through state-of-the-art approaches.
Enhancing Label Representations with Relational Inductive Bias Constraint for Fine-Grained Entity Typing

Fine-Grained Entity Typing (FGET) is a task that aims at classifying an entity mention into a wide range of entity label types. Recent researches improve the task performance by imposing the label-relational inductive bias based on the hierarchy of labels or label co-occurrence graph. However, they usually overlook explicit interactions between instances and labels which may limit the capability of label representations. Therefore, we propose a novel method based on a two-phase graph network for the FGET task to enhance the label representations, via imposing the relational inductive biases of instance-to-label and label-to-label. In the phase 1, instance features will be introduced into label representations to make the label representations more representative. In the phase 2, interactions of labels will capture dependency relationships among them thus make label representations more smooth. During prediction, we introduce a pseudo-label generator for the construction of the two-phase graph. The input instances differ from batch to batch so that the label representations are dynamic. Experiments on three public datasets verify the effectiveness and stability of our proposed method and achieve state-of-the-art results on their testing sets.
Cross-National Study on Phishing Resilience

Phishing is a ubiquitous global problem that is both the simple crime of theft of authenticating information and the first step in advanced persistent attack chains. Despite receiving worldwide attention and investments in targeted anti-phishing campaigns, a large proportion of people are still vulnerable to phishing. This is not only due to the evolution of phishing attacks, but also due to the diversity of those exposed to phishing attacks in terms of demographics, jurisdiction, and technical expertise. To explore phishing resilience, we conducted a cross-national study to identify demographic and other factors that might have an impact on phishing resilience across nations. Specifically, we recruited 250 participants from the United States, Australia, New Zealand, Canada, and the United Kingdom to observe their responses to phishing websites in a simulated environment. We identified how factors including demographics, knowledge, skills, website familiarity, and self-reported risk assessment behaviors relate to efficacy in phishing detection. While participants’ phishing knowledge, familiarity with the target website, and their reported use of the lock icon as a phishing indicator increases participants’ probability of correctly identifying a legitimate website, we found that these factors did not specifically make them more resilient to phishing attacks. Our results further show that computer expertise has a significant positive impact on phishing resilience and that increased age correlates with the probability of misconstruing a phishing site as legitimate. These findings were applicable across all five countries in our study.
Cyberbullying in Pakistan: Positioning the Aggressor, Victim, and Bystander

This study explores cyberbullying prevalence, causes, reasons, and preventive measures from the perspective of victims and bystanders. The data were gathered from 329 male and female students of different age groups through an open-ended questionnaire and cyberbullying confession pages. Constructivist thematic framework was applied to look for commonly emerging patterns in the data. The study revealed that the likelihood to become a victim to cyberbullying decreased with an increase in age. However, there was no association between gender and cyberbullying. The study showed that various linguistic resources were exploited by the aggressors to victimize the participants. However, being sophomoric users of social media sites and having offline disputes were the core reasons of cyberbullying among a majority of victims. The participants valued the support of parents and friends, and showed faith in the preventive measures taken by educational institutes and Federal Investigation Agency, Pakistan against cyberbullying assaults. Findings from this study contribute to the research on cyberbullying, which is still in its infancy in Pakistan and may help in formulating cyberbullying prevention program.
Evaluating reading comprehension ability through the SQ4R model

espanolEl objetivo de este trabajo fue evaluar las habilidades de comprension lectora de los estudiantes de V grado en Indonesia utilizando el modelo SQ4R (Encuesta, Pregunta, Lectura, Reflexion, Recitacion, Revision). Se selecciono una muestra de poblacion compuesta por 30 estudiantes a traves de un muestreo intencional en el SDN Medan Johor. Los datos fueron recolectados a traves de observaciones, pruebas previas y examenes posteriores a la prueba. El objetivo era determinar como el modelo habia influido en las habilidades de los participantes. Los resultados mostraron que el modelo SQ4R podria usarse en la escuela primaria para motivar a los estudiantes y hacerlos mas activos en clase, asi como mejorar las habilidades de comprension de lectura. EnglishThe aim of this paper was to assess the reading comprehension skills of V grade students in Indonesia using the SQ4R model (Survey, Question, Reading, Reflect, Recite, Review). A sample population consisting of 30 students was selected through purposive sampling at the SDN Medan Johor. Data was collected through observation, pre-tests, and post-test examinations. The objective was to determine how the model had influenced the abilities of the participants. The results showed that SQ4R model could be used in elementary school to motivate students and make them more active in class, as well as enhance the reading comprehension skills.
High-Performance Quantum Teleportation Systems at Telecom C-Band

Based on performance improved entangled photon pair source at 1.5 µ m, we experimentally demonstrated quantum teleportation with the rate and fidelity of 6.41±0.37 Hz and 87.70±5.75% over a state-transfer distance of 40 km.
Conception of the Cultivation Model of Innovative Talents for English Majors in Colleges and Universities Based on Constructivism

The research on the cultivation of innovative talents for college English majors from the global perspective is a hot topic at present.This article briefly describes the connotation of constructivist teaching theory and its significance to college English majors' innovative ability, and explores ways to cultivate college English majors' innovative ability.The teaching ideas for English majors under the guidance of constructivist theory require teachers to change their teaching concepts, pay attention to the cultivation of students' cross-cultural awareness, reform evaluation methods and improve teaching methods.The second is to promote normal students to carry out autonomous learning, cooperative learning and inquiry learning.Third, while paying attention to the grade examination, we should enrich the cultivation of teachers' educational theoretical knowledge and practical teaching ability, shorten the adaptation period of English Teaching in basic education, and lay the foundation for becoming an expert teacher.However, under the guidance of constructivism theory, there are some limitations in the cultivation of innovative talents, which requires colleges and universities to emphasize scientific development in the process of cultivating innovative talents.
Develop a dynamic DBSCAN algorithm for solving initial parameter selection problem of the DBSCAN algorithm

&lt;p&gt;The amount of data has been increasing exponentially in every sector such as banking securities, healthcare, education, manufacturing, consumer-trade, transportation, and energy. Most of these data are noise, different in shapes, and outliers. In such cases, it is challenging to find the desired data clusters using conventional clustering algorithms. DBSCAN is a popular clustering algorithm which is widely used for noisy, arbitrary shape, and outlier data. However, its performance highly depends on the proper selection of cluster radius &lt;em&gt;(Eps)&lt;/em&gt; and the minimum number of points &lt;em&gt;(MinPts)&lt;/em&gt; that are required for forming clusters for the given dataset. In the case of real-world clustering problems, it is a difficult task to select the exact value of Eps and &lt;em&gt;(MinPts)&lt;/em&gt; to perform the clustering on unknown datasets. To address these, this paper proposes a dynamic DBSCAN algorithm that calculates the suitable value for &lt;em&gt;(Eps)&lt;/em&gt; and &lt;em&gt;(MinPts)&lt;/em&gt; dynamically by which the clustering quality of the given problem will be increased. This paper evaluates the performance of the dynamic DBSCAN algorithm over seven challenging datasets. The experimental results confirm the effectiveness of the dynamic DBSCAN algorithm over the well-known clustering algorithms.&lt;/p&gt;
The uncertainty principle over finite fields

In this paper we study the uncertainty principle (UP) connecting a function over a finite field and its Mattson-Solomon polynomial, which is a kind of Fourier transform in positive characteristic. Three versions of the UP over finite fields are studied, in connection with the asymptotic theory of cyclic codes. We first show that no finite field satisfies the strong version of UP, introduced recently by Evra, Kowalsky, Lubotzky, 2017. A refinement of the weak version is given, by using the asymptotic Plotkin bound. A naive version, which is the direct analogue over finite fields of the Donoho-Stark bound over the complex numbers, is proved by using the BCH bound. It is strong enough to show that there exist sequences of cyclic codes of length n, arbitrary rate, and minimum distance Ω(nα) for all 0<α<1/2. Finally, a connection with Ramsey Theory is pointed out.
Influence of Augmented Reality (AR) Technology via Mobile Application for Knowledge Transfer Program in Fourth Industrial Revolution Era

Education is considered one of the impact sectors, which is a part of the Industrial Revolution 4.0 (IR4.0),where humanity and technology are aligned to empower new possibilities.Academic exploration of Augmented Reality (AR) technology and skills of IR 4.0 in schools, especially in rural areas, have been scarce.Therefore, this paper examines the influence of AR technology via mobile application on teachers and students via community-based learning approach.One rural primary school was selected for this community-based research project: Sekolah Kebangsaan Pulau Gaya in Kota Kinabalu, Sabah, Malaysia.It was selected as the school's drop-out rates have remained high and it has low student retention levels.Students here are unprepared for becoming more autonomous learners with better responsibility for organizing and planning their learning time.There were 22 teachers and 95 primary students (75 female and 20 male), aged from nine to twelve, third to sixth grades involved in this project.Their changes in attitude, practices, and skills were evaluated before and after the AR intervention.A majority showed an increase in positive preferences and enjoyment in AR learning, and in general, an increase in their STEM skills and performance.The findings show that employing an AR approach in primary students learning reveal significant differences in students' preference in AR learning, enjoyment in AR learning, performance in STEM learning, enjoyment in science learning, willingness to attend STEM classes, and STEM skills after the AR intervention.Thus, the newly developed AR learning module is an attempt to assist teachers nurture their students via this knowledge transfer program, increase their engagement, peer interactions and collaboration, and improve their confidence to become successful learners in the future.
Virtual studio 1.0: A virtual tacit-forward learning management framework

The purpose of this paper is three-fold. First, it documents the creation of a Virtual Studio learning management system that supports formal and informal tacit learning. Second, it provides a faculty reflection, and third, it presents student perceptions of the Virtual Studio in supporting an online planting methods course during COVID-19 restrictions. Survey results demonstrated strong support for using the Virtual Studio. However, students do not perceive it as a replacement of in-person instruction. Future Virtual Studios should explore the inclusion of real-time verbal communication to deepen socialand co-presence. © Wichmann Verlag, VDE VERLAG GMBH · Berlin · Offenbach.
Silicon Photonic Switch-Enabled Server Regrouping Using Bandwidth Steering for Distributed Deep Learning Training

We demonstrate SiP switch-enabled server regrouping using bandwidth steering for performance improvement in distributed deep learning training in a Fat-tree testbed. Our proposed SiP switch control scheme enables scaling to large-scale datacenter and HPC systems.
Overview Of System Development Life Cycle Models

During the time half of the twentieth century, the utilization of Programmed computers has become huge. As an outcome, software programming has turned out to be increasingly differing and complex. Also, there are expanding requests on software programming – it must be less expensive, have more usefulness, be conveyed speedier, and be of higher quality than already. In the constantly changing environment and society of programming advancement, the procedures and strategies utilized when growing little projects are not adequate while developing extensive frameworks. As one response to this, distinctive improvement lifecycle models have been characterized. This paper portrays the three fundamental sorts of systems Development lifecycle models, from the successive models using incremental models to transformative models. The iterative advancement technique is additionally examined, and we additionally intricate the association of advancement lifecycle models to two rising fields in programming designing: programming design and part-based programming advancement.
Improving Context-Aware Neural Machine Translation with Source-side Monolingual Documents

Document context-aware machine translation remains challenging due to the lack of large-scale document parallel corpora. To make full use of source-side monolingual documents for context-aware NMT, we propose a Pre-training approach with Global Context (PGC). In particular, we first propose a novel self-supervised pre-training task, which contains two training objectives: (1) reconstructing the original sentence from a corrupted version; (2) generating a gap sentence from its left and right neighbouring sentences. Then we design a universal model for PGC which consists of a global context encoder, a sentence encoder and a decoder, with similar architecture to typical context-aware NMT models. We evaluate the effectiveness and generality of our pre-trained PGC model by adapting it to various downstream context-aware NMT models. Detailed experimentation on four different translation tasks demonstrates that our PGC approach significantly improves the translation performance of context-aware NMT. For example, based on the state-of-the-art SAN model, we achieve an averaged improvement of 1.85 BLEU scores and 1.59 Meteor scores on the four translation tasks.
Knowledge Discovery in Clinical Data

The information about patients and their medical condition are stored in a large clinical database. In this data the different patterns and relationship give new medicinal learning. To find this hidden knowledge several methods and techniques are developed. The research proposed a data mining technique in huge clinical database for searching the relationships. This data mining technique is known as Knowledge Discovery in Databases. This research defines different methods and process of data mining in clinical database.
Implementasi Motor Servo MG996r Sebagai Robot Pemegang Batang Nosel Pada Sprayer Elektrik Berbasis Arduino Mega2560

The sprayer is one of the equipments that is often used in agriculture, especially in rice plants to control pests and diseases. The use of the nozzle rod on the electric sprayer still uses hands resulting in the spray distance on the rice being not constant. To answer this problem, the researcher will create an innovative robotic hand holding the nozzle rod on an electric sprayer that will direct the nozzle rod constantly. Servo MG996r as a rectifier of the motion of the nozzle stem which will determine the distance and area of ​​spraying on rice. To achieve maximum dispersion in rice with a 4:1 legowo system with a servo rod length of 50 cm and a spacing between rice of 25 cm, the servo must move forward and backward at an angle of 110° - 180° which can be seen on the LCD and the distance of the nozzle rod on the object can be up and down to 38 cm and up 24 cm from the starting position. The results obtained by the robotic hand holding the nose bridge can work optimally.
Cataloging Psychological Tests in an Academic Library

Often relegated to a side note in conversations about curriculum materials collections, psychological tests deserve their own consideration in library cataloging. Libraries that are dedicated to psychology (or psychology and a related field, such as education) lend psychological tests either for reference or for usage in clinical training programs. These libraries, largely academic, have a need for guidelines regarding the cataloging of psychological tests, as those developed under the Anglo-American Cataloguing Rules, second edition (AACR2) are no longer satisfactory for Resource Description and Access (RDA) cataloging. This paper provides an overview of AACR2 cataloging guidelines and proposes new RDA best practices when cataloging psychological assessments, including kits.