Reviewerly/exHarmony huggingface dataset:
Preserving Security, Privacy of Health Passport Over Patient in Cloud

The passport is an expandable document in which key personal, social care and clinical information is recorded. Everyday people move to difference places whether abroad or within the country and some people it might happen they forgot their health passport or they are not registered in any health sectors as a result it might be difficult to have treatment without a health passport. So we designed a Cloud health passport system which is secure, fast and private which will be helpful, using block chain algorithm to allow continuous updating by family and health professionals, acting as a ‘live’ synchronized record of changing need, service. The passport is set up by the patient (or their agreed representative) and carried on their mobile device across different healthcare settings using Dynamic Searchable Symmetric Encryption (DSSE). It stores demographic details and pertinent clinical information. By having a digital record of this information, valuable patient (and administrative) time is not wasted at registration, improving the patient experience. By incorporating an individual health identifier, it allows a patient to be readily identified across any healthcare setting. The option of storing the dates of upcoming appointments could lead to a reduction in the out-patient non-attendance rate currently estimated at 15%. The increased likelihood that important clinical information is filed to the correct patient record frees up more time for direct patient care.
Isolated Bangla Spoken Digit and Word Recognition Using MFCC and DTW

Digit recognition is one of the elegant research topics in modern world. Scientists had already got an excellent output in their research work on this topic for English and Chinese like languages. However, very few works exist on digit recognition for regional language. Moreover in case of regional language the pronunciation rapidly varies on the basis of area and the performance of their proposed recognition reasonably low. In this paper we have worked on digit recognition on a regional language, Bengali referred to as Bangla. In our proposed work of isolated digit and word recognition, we created a small speech database, containing ten Bangla digit zero to nine (pronounced as ‘sunno’ to ‘noi’) and four Bangla words (English equivalent Right, Left, Above, and Below respectively) with 100 samples for each class. We have done a pre-processing phase, followed by a 39 dimensional feature extraction procedure of Mel Frequency Cepstral Coefficients (MFCC), $$\varDelta $$ MFCC and $$\varDelta $$ $$\varDelta $$ MFCC. Finally, we used the Dynamic Time Warping (DTW) for classification of testing purpose. The system has achieved a highest accuracy of 93% for classification of Bangla words and digits, which is considerably satisfactory. The comparative analysis with the existing method is given in Sect. 5.
The Intergenerational Income Mobility of Chinese Urban and Rural Residents Based on Big Data Technology

In order to analyze the intergenerational income mobility of urban and rural residents, this paper uses big data technology to study the intergenerational income mobility of urban and rural residents in China, constructs a corresponding model, and presents an interval type-2 fuzzy model based on the distributed integration method. The model constructs an initial interval type-2 fuzzy model through a distributed integration strategy and provides an optimization method for the parameters of the interval type-2 fuzzy model based on the least squares method, which is used to ensure the prediction performance of the model. The experimental study verifies that the big data technology can play an important role in the research on the intergenerational income of urban and rural residents in China.
A Conceptual Study on Employer Perception towards Hiring Employee with Online Degree/Certification

Higher education is enduring a transition across the world. This transition leads to the introduction of technology into the education system and provides opportunities to pursue a degree through online participation. According to Bramble and Panda, globalization plays a vital role in recognizing the necessity of providing online learning opportunities in higher education. The stakeholders and education institutions are very much concerned about the massive potential of online learning models. In the span of a decade, the demand for online courses has increased due to change in technology, lifestyle, economics, concerns of employees to develop knowledge, new competency skills and thinning out the geographical differences, etc. The innovative archetype of the online education is significant in quality, course content, satisfaction, and the perception of the users from various levels when compared to traditional face-to-face classroom systems. As a result, online education is more effective and efficient than the model of face-to-face education. The main objective of this research is to analyse and measure the various factors that affect employer perception towards online education systems in their recruitment process and cycle. 549 articles have been examined in terms of integrated literature review system to measure the impact. The result indicates, awareness, readiness, credentials and reputation are the major factors that affect employer perception on hiring decision.
Haptic feedback in first person shooter video games

Immersion has become an important factor for video games. This study investigates the effect that haptic feedback has on the perceived immersion of the player in two different setups; one with haptic feedback in the game controller and one with feedback in a haptic vest. Both experiments consisted of a user test, followed by answering a questionnaire. The results show tendencies of haptic feedback both increasing and inhibiting the ability to feel immersed by certain metrics, even if the statistical analysis shows no significant difference between the groups in any of the sub-scales. The results also show that most of the test subjects thinks that the vest and its’ haptic feedback delivers more immersion to the gaming experience. The conclusion that can be drawn from both experiments is that haptic feedback improves the user feeling of immersion, more specifically regarding the players awareness of the surroundings in the game.
Bayesian Tree-Structured Two-Level Clustering for Nested Data Analysis

Data integration plays a crucial role in the era of big data. The nested data are a combined set of observations from multiple sources and exhibit heterogeneity both at the source level and at the observational level. The complex nature makes it challenging to reasonably visualize and jointly analyze the nested data. In this article, we present a nonparametric Bayesian model to implement the tree-structured two-level clustering for nested data analysis. The two-level clustering is used to tease out the heterogeneity existing in the sources and observations, while a tree-structured prior is employed to model the latent hierarchy for clusters at the observational level. The proposed Bayesian model is flexible as it does not require an exact specification of cluster numbers or tree width/depth, and it can automatically learn the underlying tree structures among clusters of observations, thus, offering an insightful visualization of the nested data. We further provide a rigorous posterior sampling scheme via the partially collapsed Gibbs sampler and show the performance of the proposed method using simulation studies. Finally, the applications to two different types of nested data (multi-source image data and multi-subject single-cell expression data) demonstrate the advantages of the proposed Bayesian method. Supplementary materials for this article are available online.
The Design of an Experiment to Evaluate the Effect of Spatial Sound on Memory Recall in a Virtual Reality Learning Environment

With the widespread availability of affordable consumer devices, Virtual Reality is fast becoming a valid solution for enabling accessible and immersive teaching and learning experiences. VR presents many educational opportunities but there are still aspects that need further investigation, one being the utilisation of sound within VR, and the effect it has on memory recall. In the context of the online learning, this paper outlines a planned experiment design to investigate the relationship between spatial sound used within an online Virtual Reality Learning Environment (VRLE) and its effect on immediate memory recall. The experiment uses an immersive, web-based platform exploiting the WebXR application programming interface, and built using Three.js and Resonance Audio JavaScript libraries. Using different audio conditions, an adapted Logic Memory test, in-VR questionnaires, and both between-group and within-group analysis, the goal of the experiment is to examine the effect of spatial audio on immediate memory recall, when compared to non-spatial audio.
”Man’s (and Sheep’s) Best Friend”: Towards a Shepherding-based Metaphor for Human-Computer Cooperation in Process Control

Metaphors can be helpful in human-computer interaction in various ways, e.g., for user-appropriate design of interfaces, naming of functions, or visualization. In the field of process control, paradigm shifts are imminent under terms such as smart control rooms or pervasive computing environments. However, there is a lack of suitable metaphors to accompany this development. This paper examines the extent to which sheep herding and the relationships between humans, dogs, and sheep can be a suitable model for shaping human-computer cooperation in process control. Even though sheep herding has already been discussed in various relationships to HCI, a systematic discussion of the factors that underlie successful human-animal cooperation is lacking. This is introduced in this paper based on an expert interview and literature research. Based on this, it is discussed to what extent the success factors can be transferred to the design of technical systems and human-computer cooperation.
A Systematic Literature Review on UCD4D Studies

The paper presents preliminary results from a systematic literature review on user-centred design initiatives for development (UCD4D). The review is motivated by our own experiences from a design project. Fifty papers from venues in human-computer interaction and software engineering are identified and analyzed. The review gives an overview about commonly used methods and techniques in UCD4D projects and analyzes faced challenges as well as assumptions and attitudes of researchers and participants.
”What Do You See Now?”: Lessons Learned While Integrating a Virtual Reality Application in Ambulatory Care of a Pediatric Surgery

In many medical contexts, virtual reality (VR) applications are associated with high hopes for improved forms of care. In order for these hopes to be fulfilled not only in controlled (laboratory) studies, possibly accompanied by technicians, but also in everyday clinical practice, applications must be suitable for the users on the one hand and efficiently integrated into the organizational processes on the other. While the first aspect has already been widely studied in terms of VR-related user interface and interaction design, there are fewer references and recommendations on the second one. These are given in this contribution. They are based on findings of applying human-centered design methods (contextual inquiry, work models, focus group) during the integration of a VR application in ambulatory care of children and adolescents after bone fractures. Finally, transferability of the recommendations to other contexts, including beyond clinical scenarios, is discussed.
State of the Art About COVID-19's Impact on Santiago University, Cape Verde

The COVID-19 pandemic has become a critical challenge for the higher education sector worldwide. Under such a circumstance, the exploration of the capacity of this sector to adapt to such a state of uncertainty has become of huge importance. In this chapter, the authors critically reflect on the Cape Verdean teaching experience during the early COVID-19 lockdown. This is an exploratory case study based on a qualitative approach with an aim to reflect on new practices of teaching under a pandemic emergency. Based on the teaching experience of teaching in Santiago University, they explain how this university has changed from a face-to-face to an online teaching system and stress the challenges and opportunities that appear from this transition process. This chapter concludes that this strategy has become an opportunity to the university since it consistently raised the number of international students cooperating with them and also that the more adaptive and resilient approaches to online teaching were also a success.
Remote Testing of an Augmented Reality System

Remote test settings have become more common due to COVID-19. Our paper presents two user tests focusing on the usability and user experience of an augmented reality-based solution, i.e., augmented reality system. We describe the proceeding of the tests from the perspective of what party has participated in the test in the same location as the test participant, i.e., locally, and what party remotely. The importance - or unimportance - of physical presence is contemplated from the perspective of the successfulness of the test. The physical presence of a person providing technical support to the test participant during the testing proved vital for the augmented reality related testing; the location of other test organisers appears more indifferent in this context.
Online Learning Support in a Ubiquitous Learning Environment

The ubiquitous learning environment (ULE) is both an ontological and epistemological problem. For most scholars, ULE provides an interoperable, pervasive, and seamless learning architecture to connect, integrate, and share three major dimensions of learning resources: learning collaborators, learning contents, and learning services. Furthermore, ULE is described as an educational paradigm that mainly uses technology for curriculum delivery. Through reflection and exploration, this chapter argues that online learning support has a symbiotic relationship with ULE because the student, at some point, should move beyond the “text” level into concepts and conceptual organization schemes (ontologies). In line with this viewpoint, this chapter problematizes the gap created by real-world and digital-world resources—and argues that online learning support for teaching and learning processes have not yet emulated ULE as an important pedagogical resource.
Social Media Bots, Trolls, and the Democratic Mandates in Sub-Saharan Africa

This exploratory study investigates the role that bots and trolls played on social media in widening the gaps of political partisanship in sub-Saharan Africa. Taking the case of the 2018 Zambian by-elections, the authors examined the relationship between online social media content that propagates hate and organized trolling efforts in Zambia. The study used machine learning tools to identify the origin of the bots on Facebook and Twitter accounts (trolls) of the two major political parties in Zambia (PF and UPND). Online posts that accounted for the election campaigns and the aftermath in the year 2018 were considered for the study. Findings suggest that social-mediated conversations were divided along political lines and that the examined trolling accounts systematically took advantage of the existing echo chambers to create hate messages on Zambian social networks. In other words, the findings indicated that the online hate messages that accounted for violence were neither created by the PF or UPND political parties as earlier studies suggest but by bots and trolls.
The Pragmatics of Political Deception on Facebook

Facebook, an intrinsic part of 21st century social realities where cognitive-participatory activities are largely captured, is consistently explored for political deception. This chapter investigates how participants utilize language to deceive politically the Nigerian electorate on Facebook. For data, 250 Facebook posts on Nigerian politics were sampled, out of which 50 were purposefully selected for being highly rich in deceptive content in order to unpack online deception through multimodal critical discourse analysis. Four deceptive forms—equivocation of identity, exaggeration of performance, falsification of corruption cases, and concealment of offences—within two socio-political contexts—election and opposition—constituted the posts. These prompt an evocation of a messianic figure, blunt condemnation, and evocation of sympathy and retrospection to achieve the political intentions of criticism, self-presentation, silent opposition, and galvanizing public support. The chapter concludes that political propaganda taps into Facebook users to appeal to their political biases and sway their opinions.
Online and Distance Education in the Era of Rampant Technological Revolution

Developments in information and communication technologies have reached an all-time high. These improvements have accelerated the transformation of higher education milieus on all sides. Accordingly, higher education institutions have begun to be delineated by these technological developments, activities, and practices. This technoculture era has started a new interaction among communication technologies, teachers, and learners. Herein, transhumanism regards changes in societies through these technological interactions and transformations. The worldwide technological transformation is approximating all societies and cultures to Marshall McLuhan's notion of a global village day by day as a consequence of the technology paradigm. The heydays of the developments in technologies affect all human beings at all points from living, learning, communicating to eating and even thinking styles. Taking these points into account, this chapter will explore how these variables may influence the online distance education milieus in terms of technoculture and transhumanism perspectives.
Failure of Governance, State Legitimacy, and Hate Speech in Ethiopia

Despite social media has supplied a great role in bringing the current political landscape of Ethiopia, a couple of months after PM Dr. Abiy took hold of power, hate speech on social media has become common. This has made the government police social media by drafting laws on hate speech since April 2019. This study has the objective of exploring the interplay between spoil political system, government legitimacy and hate speech on social media. This study adopted qualitative research approach. Data has been gathered data from social media e.g. Facebook, Twitter, and Telegram. Different pages and informal discussions were important tools of data collection. From the findings, the author concludes with the argument that laws are not effective to end hate speech, but can be done by bringing legitimate government, good governance, equality, and justice to the country.
Using Twitter to Characterize Public Opinion in Brazil During Political Events

In this work, the authors characterize Brazilian online population sentiment on different political events using data from Twitter and discuss the advantages of the usage of this social media as a data source. The results demonstrated that the Brazilian population uses Twitter to manifest their political view, expressing both positive and negative sentiments regarding political events. This kind of characterization may contribute to build a critical opinion of Brazilian people, once they would not be limited by what is being divulgated by typical media, such as television and newspapers. Additionally, the authors reinforced the applicability of social media, as Twitter, to make this kind of characterization.
Gauging Opinions About the Citizenship Amendment Act and NRC

Today, the advent of social media has provided a platform for expressing opinions regarding legislation and public schemes. One such burning legislation introduced in India is the Citizenship Amendment Act (CAA) and its impact on the National Citizenship Register (NRC) and, subsequently, on the National Population Register (NPR). This study examines and determines the opinions expressed on social media regarding the act through a Twitter analysis approach that extracts nearly 18,000 tweets during 10 days of introducing the scheme. The analysis revealed that the opinion was neutral but tended to a more negative reaction. Consequently, recommendations on improving public perception about the scheme by suitable for interpreting the Act to the public are provided in the paper.
A Novel Dual Image-Based Reversible Hiding Technique Using LSB Matching-Digital World

The term internet has become more popular these days, and the whole world is connected virtually. Most people communicate through the internet. Communicating information from one to another in network without disclosing to third party is a typical task, but tracking of information is performed when certain security measures are not taken during transmission between the real-time environment and virtual environment. Creation of virtual representation for real-time process is known for the digital world. Secret data communication is performed under the digital world concept where there is a need of security. The chapter introduces a mechanism providing security using the ISDHR technique with least significant matching and dual images for secret message communication. The results show the proposed method is high enough in providing security to the secret data under transmission.
A points of interest recommendation framework based on effective representation of heterogeneous nodes in the Internet of Things

Location-based social networks are a special kind of the Internet of Things in which users and points of interest (POIs) are heterogeneous network nodes. When matching POIs for users, traditional recommendation methods either map users to POI space or map POIs to user space. This direct mapping of the heterogeneous space introduces some noise to the node representation. The sparse interaction between users and POIs makes it difficult to effectively distinguish the representations of similar heterogeneous nodes. Based on the above problems, this paper proposes a recommendation framework that projects heterogeneous network nodes: users and POIs into a unified representation space. Obtain the matching results of nodes in the new problem space and effectively solve the problem of unified representation of heterogeneous nodes in the Internet of Things. The setting of the intermediate latent space can distinguish the representations of similar behavior nodes as much as possible and obtain more accurate recommendation results. We conduct extensive experiments on a four real-world datasets which show that framework has superior performance compared to the state-of-the-art framework for POI recommendation.
Turbulent Flow Estimation by Wavelet Transform

Turbulent flow estimation from an image sequence is challenging due to the lack of dedicated flow measurement techniques. Existing techniques estimate flowrate with high uncertainty. In this paper, a new technique based on discrete wavelet transform (DWT) is proposed. Wavelets have the advantage of decomposing flow signals into numerous levels and remove input signal noise. The flow signals are first decomposed using DWT into multiple levels, then, the wavelet coefficients are correlated by the Fast Fourier Transform (FFT) based algorithm to determine the velocity field. This wavelet-based algorithm is named as DWT-FFT. DWT-FFT was evaluated first using synthetic signals and then applied for turbulent flow estimation. The accuracy of DWT-FFT was compared to classical algorithms including direct cross correlation (DCC) and direct implementation of FFT. DWT-FFT estimated the flow with an error of 0.7%, outperforming both DCC and FFT which estimated with an error of 7.14% and 12.2% respectively.