Reviewerly/exHarmony huggingface dataset:
Mapping contexts of care

Healthcare today increasingly involves patients using various devices to engage in different care activities and often doing so without the aid of trained healthcare professionals. This situation means patients must often use health and medical information (i.e., content) in various contexts with different dynamics. As a result, usability – or how effectively individuals can use items – becomes central to effective medical communication. Usability expectations affecting such communication dynamics are often guided by psychological processes reflecting prior healthcare experiences. Meeting these expectations involves identifying the cognitive factors influencing how individuals use materials. This conceptual paper examines how the psychological concept of ‘cognitive scripts’ can help address such situations. The paper also presents an approach for identifying the cognitive scripts affecting usability expectations and applying this information to create usable communication materials for healthcare contexts.
ElMinia University first breast cancer screening experience, Egypt

Introduction: Breast screening is the most beneficial way to detect breast cancer early and to have best therapeutic response. This is the first screening study for breast cancer in Minia University Hospital as a retrospective study held in Minia University between March 2018 and January 2019 in collaboration with national project for women health. The breast sonomammography combination is more beneficial as regarding the diagnostic indices, reducing the recall rate and patients’ stress, the availability of any further assessments at the same visit and saving transportation, so sonomammography is the suitable screening protocol in our society.
First steps into coherent object classification using convolutional deep diffractive neural networks

Abstract As artificial intelligence and deep learning becomes more important, new approaches for photonic neural computing arise. We investigate the concept of deep diffractive neural networks. First proposed in 2018, deep diffractive neural network operate passively, using coherent images and diffractive optics to do image-to-image regression and object classification. In this article we shortly review current approaches, give a brief introduction into the mathematical description of such diffractive networks using the Angular Spectrum method and show the first results of our own developments of convolutional diffractive networks with an experimental accuracy of approximately 84 %. The objective of this article is to give an introduction into the field of optical computing with neural networks using diffraction and free-space propagation of light.
Data Transmission in Wearable Sensor Network for Human Activity Monitoring using Embedded Classifier technique

The recent development of wireless wearable sensor networks has opened up a slew of new possibilities in industries as diverse as healthcare, medicine, activity monitoring, sports, safety, human-machine interface, and more. The battery-powered sensor nodes' longevity is critical to the technology's success. This research proposes a new strategy for increasing the lifetime of wearable sensor networks by eliminating redundant data transmissions. The proposed solution is based on embedded classifiers that allow sensor nodes to determine whether current sensor readings should be sent to the cluster head. A strategy was developed to train the classifiers, which takes into account the impact of data selection on the accuracy of a recognition system. This method was used to create a wearable sensor network prototype for human monitoring of activity Experiments were carried out in the real world to assess the novel method in terms of network lifetime, energy usage, and human activity recognition accuracy. The proposed strategy allows for a large increase in network lifetime while maintaining excellent activity detection accuracy, according to the results of the experimental evaluation. Experiments have also demonstrated that the technology has advantages over state-of-the-art data transmission reduction strategies.
Peer Review Statement

All papers published in this volume of Journal of Physics: Conference Series have been peer reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. • Type of peer review: Double-blind • Conference submission management system: All the papers were submitted papers via the conference email: submission@4th-msota.org • Number of submissions received: 163 • Number of submissions sent for review: 142 • Number of submissions accepted: 64 • Acceptance Rate (Submissions Accepted / Submissions Received × 100):39.3% • Average number of reviews per paper: 2 • Total number of reviewers involved: 53 • Any additional info on review process: MSOTA2021 uses the iThenticate software to detect instances of overlapping and similar text in submitted manuscripts. • Contact person for queries : Kennis Chan, Advanced Science and Industry Research Center, Hong Kong, submission@4th-msota.org
TECHNOLOGY FOR CREATING A DOMAIN KNOWLEDGE BASE OF QUESTION-ANSWERING SYSTEM BASED ON A LARGE-SCALE UNIVERSAL KNOWLEDGE BASE

Usage of question-answering systems has become a popular way to access knowledge bases that contain a large number of facts from different domains. Large-scale universal knowledge bases with open access, such as Wikidata, contain huge collections of facts. Although those bases cover the most significant part of the accumulated humankind knowledge, there are a number of reasons why their direct usage in question-answering systems can be less preferable than the creation of specialized domain knowledge bases based on them. This paper presents a technology for building a domain knowledge base for a dialogue system based on domain boundaries detection from an open large-scale universal knowledge base. It is based on a multi-step process of analyzing a large number of free-form questions on a given subject area that were collected using a crowdsourcing platform. The technology includes the correction of the original knowledge base ontological structure and its filling with additional content. The proposed technology is invariant to the original knowledge base and the modeling subject area. We tested it on the Wikidata knowledge base and six subject areas.
Convergence the Experiences

The consumer experience is available and embedded in future ready entertainment hardware and technologies along with the creative software and talents of the producers and programmers that flip the switches and pull the leavers that craft the magic. Virtual reality (VR), augmented reality (AR), mixed reality (MR), extended reality (ER) and 360 Video are proven experiences already in use for entertainment and education, but it still seems that large high resolution fixed screen monitors continue to be the picture and viewing experience of preference. The New Realities Experience is resulting in a complete convergence of different electronic delivery platforms that will include ultra high definition (UHD) pictures with interactive touch screens, motion control, immersive sound along with headphones, goggles, gadgets and more – true integration.
Students Shaping Their Future

Based on the Technological Acceptance Model, this chapter aims to propose a case study to expand the body of knowledge concerning the adoption of virtual reality applications as e-learning tools. Lockdowns to contain the spread of the COVID-19 pandemic are posing many challenges of how to improve STEAM-based curriculum design so as to provide students with an array of significant life skills to meet the shifting labour-market demand and embrace the hybrid intelligence that is expected in their future workplace. The case study is developed based on a sample tourism postgraduate student during the course of 2020–2021 that were asked to design and create a VR tour as part of the subject final task. After, students were requested to voluntarily answer an online questionnaire. Findings confirm that students’ attitude toward using VR Tour Creator tool strongly influences their intention to use it, the impact of perceived usefulness on satisfaction and the effect of perceived ease of use on perceived usefulness. The rest of the six effects are rejected; suggesting that virtual reality tools for the creation of tours are still in their infancy and that the developers of these tools should consider the knowledge presented in this chapter to improve their e-learning performance.
How does the first buggy file work well for iterative IR-based bug localization?

Information-retrieval-based bug localization (IRBL) generates a ranked list of source files by using bug reports as queries and provides the list to developers to reduce debugging costs. The IRBL performance is typically evaluated by batch because the evaluation process considers the first ranked list as the final ranked list for developers. This process assumes that the developer only examines the ranked list once. However, in this conventional IRBL evaluation process, the knowledge acquired by the developer through examining the ranked list is omitted. Disregarding this knowledge limits the development of IRBL techniques for effectively reducing effort in identifying all buggy files. An iterative IRBL evaluation process that considers knowledge acquisition based on developer feedback is proposed herein. In this iterative IRBL, it is discovered that the first buggy file is a better-quality query than the bug report. Hence, we propose a boosting method for IRBL using the first buggy file. We analyze five IRBL methods using 5,290 bug reports obtained from 156 projects. By performing large-scale experiments, we demonstrate that our boosting method improves the mean average precision from 6% to 17% and reduces the effort in localizing both the second and final buggy files. Our evaluation process facilitates the development of an IRBL method that can effectively reduce the effort required to locate all buggy files.
Unsupervised anime avatar sketch colorization based on reuse discriminators for encoding

Sketch or line art coloring is a research field with great market demand. Although the effect of some previous coloring methods is effective, it is easy to have the problem of color mixing in the facial area. In this method, based on our previous work, we use the latest image conversion framework NICE-GAN instead of CycleGAN to make the network framework more compact, and apply the multi-scale discriminator structure to make the conversion effect have more information and higher training efficiency. At the same time, combined with the attention mechanism module in the previous work, the model can learn the key coloring in the facial features area through the feature map, so as to reduce the surrounding color mixing. At the same time, due to the use of unsupervised network, the whole process is fast and automatic. It can be used for quick coloring of user-defined animation avatars. It is very friendly to novice users who can't color. The final experiment also proves that this method has better effect in facial region than other previous line drawing coloring methods, significantly reduces color mixing, and has higher training efficiency.
LOW COST REAL-TIME COLONOSCOPY PROCESSING WITH DEEP LEARNING

Aims Developing a low cost microsystem that can automatically identify in real-time different entities during a colonoscopy. It is based on a pre-trained deep learning neural network retrained on 700 annotated frames. The trained network works on a Jetson Xavier NX microsystem from NVIDIA.
Enhanced Entertainment ExperiencesSound Design for Sports

Sound design is usually interconnected to the type of media the specific aural landscape model is intended for. Essentially sound design involves the artistic and creative skills of storytelling along with enough technical knowledge and expertise to implement the sound design. After reading this book you should be able to easily sit down and write your sound vision and have the technical savvy to execute your design.
Motion Sickness in Automated Vehicles: Principal Research Questions and the Need for Common Protocols

Motion sickness in automated vehicles represents a key Human Factors concern that will negatively impact the passenger experience and, ultimately, public acceptance.Minimising or avoiding motion sickness altogether therefore becomes a strategic design goal.In this paper we propose principal research questions that need to be addressed as part of a concerted effort to understand the causative factors of motion sickness and the need to develop and apply common protocols to accelerate knowledge and subsequent innovation in this field.With the ultimate goal to provide guidelines to inform the design of future vehicles, the International Standard ISO 2631-1 (1997) is taken as the starting point.The current Standard provides estimates of the likelihood of motion sickness as a function of vertical motion input only.However, in the context of automated vehicles, and in particular in the light of anticipated Non-Driving Related Activities in such vehicles, the current standard is of limited use: The model has not been validated for horizontal and rotational motions or any potential multi-axes interactions; The Standard was derived on the basis of the percentage of passengers reaching the point of emesis while less severe levels of motion sickness are of greater interest and may show a different relationship between the frequency and acceleration; Modulating factors that are able to regulate, adjust or adapt sickness levels are not included, in particular vision and the associated concept of anticipation, passenger orientation and reclination angles.Finally, the accumulation of motion sickness knowledge in this field is severely hampered by the absence of consistent study protocols.We here propose the identification and development of appropriate vibration measurements and motion sickness assessment and evaluation methods.
Uncertainty-Autoencoder-Based Privacy and Utility Preserving Data Type Conscious Transformation

We propose an adversarial learning framework that deals with the privacy-utility tradeoff problem under two types of conditions: data-type ignorant, and data-type aware. Under data-type aware conditions, the privacy mechanism provides a one-hot encoding of categorical features, representing exactly one class, while under data-type ignorant conditions the categorical variables are represented by a collection of scores, one for each class. We use a neural network architecture consisting of a generator and a discriminator, where the generator consists of an encoder-decoder pair, and the discriminator consists of an adversary and a utility provider. Unlike previous research considering this kind of architecture, which leverages autoencoders (AEs) without introducing any randomness, or variational autoencoders (VAEs) based on learning latent representations which are then forced into a Gaussian assumption, our proposed technique introduces randomness and removes the Gaussian assumption restriction on the latent variables, only focusing on the end-to-end stochastic mapping of the input to privatized data. We test our framework on different datasets: MNIST, FashionMNIST, UCI Adult, and US Census Demographic Data, providing a wide range of possible private and utility attributes. We use multiple adversaries simultaneously to test our privacy mechanism - some trained from the ground truth data and some trained from the perturbed data generated by our privacy mechanism. Through comparative analysis, our results demonstrate better privacy and utility guarantees than the existing works under similar, data-type ignorant conditions, even when the latter are considered under their original restrictive single-adversary model.
William Gibson’s Debt to the Culture of Curiosity: The Wunderkammer, or, Who Controls the World?

Zofia KolbuszewskaWilliam Gibson's Debt to the Culture of Curiosity: The Wunderkammer, or, Who Controls the World?Polish Journal for American Studies, vol. 12 (Autumn 2018), pp. 291-306Abstract: The article discusses transformations in William Gibson's employment of the theme and poetics of the Wunderkammer from his two early novels, Neuromancer (1984) and Count Zero (1987), to Zero
William B. Carpenter, ‘On the Zoetrope and its Antecedents’ [Extract]

All the devices by which motion is given to the spectra in the Phenakisticope and Stroboscope are constructed upon these two principles; movements of translation, forwards or backwards, being determined by a difference between the number of figures disposed in circular series and the number of slits through which they are viewed; and movements in the parts of figures being produced by varying the disposition of those parts, either gradationally or interruptedly, as the effect may require. The Zoetrope has the double advantage of enabling a large number of spectators to witness its curious effects at the same time; and of serving for the ready exhibition of any number of different designs, which are printed on long strips of stiff paper, so that one can be easily substituted for another.
A summary of the research on whale optimization algorithms

Whale optimization algorithm (WOA) has the advantages of simple implementation, few adjustment parameters, strong optimization ability, and fast convergence speed, and has been widely used. Currently, it is mainly used in image segmentation, feature selection, model prediction, path planning, production scheduling and other fields. But there are also shortcomings such as easy to fall into local optimum and low convergence accuracy. Therefore, research on the improved whale algorithm has important theoretical significance and practical value. This article describes the basic principles, algorithm flow and characteristics of the whale optimization algorithm, analyzes the range of algorithm parameters and their impact on algorithm performance, and reviews the algorithms in recent years from three aspects: algorithm hybridization, operator improvement, and parameter optimization. The improvement ideas and development trends of the algorithm point out the next research direction of the algorithm.
Balloon detects first signs of ‘sound tunnel’ in the sky

Atmospheric analog to ocean's acoustic channel could be used to monitor eruptions and bombs.
SAi: an experimental incubator for informal science learning initiatives

Informal STEM learning (ISL) programs propel the connections between science and society. The STEM Advocacy Institute (SAi) is an experimental incubator that is addressing the ongoing challenges faced by founders of such initiatives. The holistic model used by the institute can be both scaled and replicated in other contexts to nurture novel ideas and projects in ISL.
A Study on Students’ Perspective towards Cooperative Learning in the ESL Classroom

In this era, there are varieties of approaches to teaching English as Second Language (ESL) learners, and there have been many types of research done to test the effectiveness of these approaches. This research aimed to examine the students’ perspectives on cooperative learning in the ESL classroom. Cooperative learning refers to various instructional practices that encourage students to work together as they apply course material to answer questions, solve problems, or create a project. Therefore, cooperative learning is different from the traditional learning approach because it expands the second language acquisition by providing room for both language input and output. This study employed the quantitative approach where 107 Diploma students from Sultan Idris Education University who underwent a compulsory English course were requested to participate in a survey after completing the activities, which incorporated cooperative learning. The questionnaire was adapted from previous research to ensure reliability in collecting data. Then, the data were tabulated using SPSS software. It focused on the students’ perspectives on learning experience, comprehension, and interaction. The findings revealed that most students had a positive perspective toward cooperative learning in the ESL classroom.
The Impact of Employing the Automation System of Paperwork on the Performance Level from the Point of View of Jeddah Municipality Staff Members: A Field Study

Abstract: This study aimed at examining the impact of employing the automation of paperwork on the performance level from the point of view Jeddah municipality staff members. To this end, the study utilized the analytical descriptive approach. The total number of the study sample consisted of (1375) staff members, whose ranks varied between the seventh and tenth ranks. A random sample of 300 staff members was selected. The study questionnaire was distributed for the sake of collecting data. (SPSS) was used to analyze the results. Eventually, several results were concluded, the most important of which is the fact that municipality staff members have the necessary expertise and competence to carry out the required tasks. The researchers recommend more development of administrative work in line with E-management objectives. Keywords: automation, performance level, paperwork, Jeddah Municipality
4-VARIABLE BOOLEAN FUNCTIONS REPRESENTATIONS CLASSIFICATION IN THE FORM OF NONLINEARITY MINIMAL DEGREE SEPARATING SURFACES

In this paper, a classification study was carried out on the construction of 4-variable Boolean functions representations classification in the form of nonlinearity minimal degree separating surfaces. To construct these surfaces was used an adaptive ellipsoid algorithm based on the Khachiyan algorithm for solving systems of linear inequalities with integer coefficients. To define Boolean functions, we used its graphical representation on the projection of a four-dimensional cube. The classification study carried out was not limited only to the search for a separating surface of the minimum degree of nonlinearity. Additionally, the task was set to find the surface with the smallest number of non-zero nonlinear terms in accordance with a given lexicographic order. Based on the results of the study, a catalog of separating surfaces of the nonlinearity minimum degree with the smallest number of nonlinear terms for Boolean functions of 4 variables is constructed, and it is also determined that 15 classes of geometric equivalence functions have a minimum degree of nonlinearity of 1, 166 - degree 2, 40 - degree 3, and 1 function degree 4.
Serving Up Sound: Treadwell mixes it up at warner bros. studio

Form a band, hit the recording studio, and make it big in the entertainment business; it’s the dream of garage bands, American Idols, and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">The Voice</i> contestants around the world. But joining a band in Smyrna, Georgia, provided an unexpected detour to success for Warner Bros. Studios Automated Dialogue Replacement (ADR) Mixer Tami Treadwell.