Reviewerly/exHarmony huggingface dataset:
An Image Privacy Protection Algorithm Based on Adversarial Perturbation Generative Networks

Today, users of social platforms upload a large number of photos. These photos contain personal private information, including user identity information, which is easily gleaned by intelligent detection algorithms. To thwart this, in this work, we propose an intelligent algorithm to prevent deep neural network (DNN) detectors from detecting private information, especially human faces, while minimizing the impact on the visual quality of the image. More specifically, we design an image privacy protection algorithm by training and generating a corresponding adversarial sample for each image to defend DNN detectors. In addition, we propose an improved model based on the previous model by training an adversarial perturbation generative network to generate perturbation instead of training for each image. We evaluate and compare our proposed algorithm with other methods on wider face dataset and others by three indicators: Mean average precision, Averaged distortion, and Time spent. The results show that our method significantly interferes with DNN detectors while causing weak impact to the visual quality of images, and our improved model does speed up the generation of adversarial perturbations.
Intelligent Planning of Spatial Analysis Process Based on Contexts

Spatial situations are the subject of analysis in many life support systems, manufacturing and business. Finding a solution of applied problem in conditions of lack of information gives rise to an interactive process of studying the situation, the participants of which are the user-analyst and geoinformation service. In the process of interaction, the analyst seeks to achieve situation awareness sufficient to generate, evaluate and make rational decisions. This paper explores the functioning of an intelligent recommender system designed to reduce the cognitive load on the user. At the heart of its work is planning a sequence of analysis contexts. The context refers to the information structure necessary for the presentation of cartographic information to the analyst. It is assumed that the geoservice has a set of contexts, and each analysis session is a time series of contexts. The problem of minimizing the number of contexts providing the necessary situational awareness of the analyst is considered. The presentation of the experience of analysis by the components of level, trend and rhythm is proposed. The results of an experimental study of the proposed method are presented too.
Leveraging Bayesian networks and information theory to learn risk factors for breast cancer metastasis

Even though we have established a few risk factors for metastatic breast cancer (MBC) through epidemiologic studies, these risk factors have not proven to be effective in predicting an individual's risk of developing metastasis. Therefore, identifying critical risk factors for MBC continues to be a major research imperative, and one which can lead to advances in breast cancer clinical care. The objective of this research is to leverage Bayesian Networks (BN) and information theory to identify key risk factors for breast cancer metastasis from data.We develop the Markov Blanket and Interactive risk factor Learner (MBIL) algorithm, which learns single and interactive risk factors having a direct influence on a patient's outcome. We evaluate the effectiveness of MBIL using simulated datasets, and compare MBIL with the BN learning algorithms Fast Greedy Search (FGS), PC algorithm (PC), and CPC algorithm (CPC). We apply MBIL to learn risk factors for 5 year breast cancer metastasis using a clinical dataset we curated. We evaluate the learned risk factors by consulting with breast cancer experts and literature. We further evaluate the effectiveness of MBIL at learning risk factors for breast cancer metastasis by comparing it to the BN learning algorithms Necessary Path Condition (NPC) and Greedy Equivalent Search (GES).The averages of the Jaccard index for the simulated datasets containing 2000 records were 0.705, 0.272, 0.228, and 0.147 for MBIL, FGS, PC, and CPC respectively. MBIL, NPC, and GES all learned that grade and lymph_nodes_positive are direct risk factors for 5 year metastasis. Only MBIL and NPC found that surgical_margins is a direct risk factor. Only NPC found that invasive is a direct risk factor. MBIL learned that HER2 and ER interact to directly affect 5 year metastasis. Neither GES nor NPC learned that HER2 and ER are direct risk factors.The results involving simulated datasets indicated that MBIL can learn direct risk factors substantially better than standard Bayesian network learning algorithms. An application of MBIL to a real breast cancer dataset identified both single and interactive risk factors that directly influence breast cancer metastasis, which can be investigated further.
Experiences and outcomes of craft skill learning with a 360° virtual learning environment and a head-mounted display

Virtual reality environments (VLEs) such as 360° videos have been introduced as educational tools over the last few years, although the pedagogical value of these media has not been widely examined, especially in the context of craft skill learning. Moreover, emotions and competences have a great impact on the usability and adoption of ICT - and on learning. In this paper, mixed-method strategies were used to address these pedagogical and emotional needs in the context of craft learning and 360° VLE. Furthermore, a quasi-experimental design was used to compare learning outcomes of 360° VLE and traditional groups. Findings based on quantitative analysis suggest that negative or positive ICT-attitude did not affect how students experienced traditional or 360° lessons emotionally. However, ICT- and craft-competences had significant correlations with the described emotions. No significant differences in terms of learning outcomes were observed between the traditional and 360° teaching methods. According to the thematic analysis of the interviews, the 1st-person-view 360° VLE could be used for basic skill observation and visualization to support traditional hands-on learning. Moreover, a head-mounted display was considered to help with focusing on the demonstration. However, more interaction with the interface and opportunities for direct interaction with the instructor were seen as necessary in 360° VLEs for skill learning in the future.
A paleolimnological approach for interpreting aquatic effects monitoring at the Diavik Diamond Mine (Lac de Gras, Northwest Territories, Canada)

(2020). A paleolimnological approach for interpreting aquatic effects monitoring at the Diavik Diamond Mine (Lac de Gras, Northwest Territories, Canada) Lake and Reservoir Management: Vol. 36, Paleolimnology, pp. 297-313.
Cervical Cancer Single Cell Image Data Augmentation Using Residual Condition Generative Adversarial Networks

Early detection of cervical cancer is key to detecting and treating cancer. Applying the computer to the detection of cervical cancer can get more accurate results. However, data acquisition has become our main challenge. In order to solve the problem of insufficient data, this paper proposes a method based on residual network and generative adversarial network (RCGAN) for data augmentation of cervical single-cell images. At the same time, our experimental results are verified by a classification model. Experiments show that the method proposed in this paper can effectively expand the data set and improve the classification effect (accuracy rate is 95.18%, accuracy is 96.10%, recall rate is 98.50%, and F1-Score is 97.28%). Therefore, the work of this article is of great significance for the discovery and prevention of cervical cancer.
A New Image Encryption and Decryption Technique using Genetic Algorithm and Residual Numbers

The security of digital images has attracted serious attention lately. In this paper, we present a novel three-layered image encryption and decryption scheme capable of encrypting and decrypting different images of variant dimensions using Genetic Algorithm (GA) and some inherent properties of the Residue Number System (RNS). This new proposed GARN scheme has a very wide key space composed at different stages of the scheme. The proposed scheme has been tested on different images and the simulated results show that the scheme can withstand cryptographic attacks, has a good throughput rate and the simulated output is chaotic enough to detect any underlying pattern. Due to the residue bits employed in this scheme, its power dissipation is also minimal.
A Framework for Assessing and Selecting Blockchains at Runtime

The suitability of a blockchain for a given use case mainly depends on the user's requirements and on the blockchain's functional and non-functional properties. Requirements and a blockchain's properties may change over time, and thus, a selected blockchain may become unsuitable for a given use case. Such uncertainties pose significant risks for developers. In this paper, we present a framework that allows developers to define functional and non-functional requirements, monitors several blockchains and, based on the specified requirements, selects the best-fitting blockchain for a particular use case. If another blockchain becomes more appropriate during runtime, the framework enables a switchover to this blockchain. Our evaluation using a reference implementation shows that switching to another blockchain can save cost and enable developers to benefit from better performance and a higher level of trust.
The Effect of Facial Expressions on Interpersonal Space: A Gender Study in Immersive Virtual Reality

In proxemics, the interpersonal space is the optimal social distance between individuals. Evidence has shown that the emotional facial expressions and gender-related effects can modulate this distance during social interactions. Typically, this distance increases in threatening situations and decreases in safe situations. Moreover, male dyads maintain larger distances than female dyads whereas the findings about mixed-sex dyads are still unclear. Virtual Reality (VR) based technologies are becoming more and more used in different areas of everyday life and, in the scientific field, for studying social phenomena. This raises the question of the degree of similarity of VR simulations to actual phenomena, i.e. its ecological validity and its effectiveness for applied purposes. In order to clarify gender-related and emotion-related effects and the ecological validity of VR, we investigated if real females and males differently modulated their interpersonal distance while male and female virtual confederates with happy, angry and neutral faces approached them. Results showed that participants preferred larger distances with both male and female virtual confederates who showed an angry face rather than neutral and happy. Moreover, males preferred a shorter distance, particularly when facing smiling virtual females, while females preferred a larger distance from angry virtual males. These results suggest that gender differences can affect the impact of emotional facial expression on the modulation of the interpersonal space. Moreover, they confirm previous behavioural studies and add further support to the ecological validity of IVR simulations and thus its potential effectiveness as a tool for research and application interventions.
An Institutional Theory Perspective on Developing a Cyber Security Legal Framework: A Case of Saudi Arabia

In the information age, the cyber-attacks have increased manifold, and developing a cyber-security legal framework is the need of the hour.Saudi Arabia experiences the highest cyber-attacks in the Arab region.This research attempts to develop a cyber-security legal framework for Saudi Arabia in particular and other countries in general.The study uses coercive, normative, and mimetic forces of institutional theory for this endeavor.Coercive pressure manifests in legal instruments, so countries like Saudi Arabia need to ensure compliance of their organizations to their respective laws, regulations, security policies, and procedures.Normative force manifests in professional networks and community expectations.So, countries like Saudi Arabia should collaborate, share information with other countries and join the Budapest Convention to combat cyber-crimes.Saudi Arabia should sufficiently incorporate the provisions of the Arab Convention on Combating Information Technology Offences in its legal instruments.Mimetic force involves copying the actions and practices of successful organizations.So, countries like Saudi Arabia should improve their legal tools by incorporating key features of legal instruments of more advanced cyber-secure nations like the UK, USA, Singapore, etc. Specifically, Saudi Arabia should improve its legal tools in the areas of privacy, identity theft, cyber-bullying, etc.
A Comparative Usability Study of Blackboard and Desire2Learn: Students’ Perspective

Educational institutions currently favor the adoption and use of modern information and communication technology for teaching and learning. As a result, many Learning Management Systems (LMS), which are online, content-management systems specifically designed to fulfil this function, have been developed over the few years and established in education systems. This paper reports the results of a study that experimentally compared the usability of two LMSs: Blackboard (BB) and Desire2Learn (D2L), at Umm Al-Qura University in the Kingdom of Saudi Arabia. The comparison involved four points: the quantity and quality of usability problems discovered, effectiveness of the targeted systems, their efficiency, and users’ satisfaction. The results of the study revealed that there are significant differences between the two systems. The evaluation discovered a higher number of major usability problems on BB. Participants were also significantly faster in completing their tasks on D2L, made fewer errors and mouse clicks, and visited fewer pages to achieve the task on D2L than on BB. However, interestingly no difference was found between the two systems in terms of users’ satisfaction. Taken together, the findings suggest that appropriate customization of Blackboard should be considered in order to enhance its usability and meet the specific requirements of its end users at the current institution.
MeSH-Based Semantic Indexing Approach to Enhance Biomedical Information Retrieval

Abstract Owing to the tremendous size of electronic biomedical documents, users encounter difficulties in seeking useful biomedical information. An efficient and smart access to the relevant biomedical information has become a fundamental need. In this research paper, we set forward a novel biomedical MeSH-based semantic indexing approach to enhance biomedical information retrieval. The proposed semantic indexing approach attempts to strengthen the content representation of both documents and queries by incorporating unambiguous MeSH concepts as well as the adequate senses of ambiguous MeSH concepts. For this purpose, our proposed approach relies on a disambiguation method to identify the adequate senses of ambiguous MeSH concepts and introduces four representation enrichment strategies so as to identify the best appropriate representatives of the adequate sense in the textual entities representation. To prove its effectiveness, the proposed semantic indexing approach was evaluated by intensive experiments. These experiments were carried out on OHSUMED test collection. The results reveal that our proposal outperforms the state-of-the-art approaches and allow us to highlight the most effective strategy.
Culture-driven emotional profiles and online discourse extremism

Abstract Discourse practices are investigated in English and Polish online comments which display different degrees of linguistic extremism. The present contribution identifies the contexts and targets of such practices and argues that hate speech is conditioned by culture-driven emotional experience and emotion expression profiles prevailing in particular societies. The discussion focuses on Polish and UK English emotionality and on relevant cultural models of the negative emotion clusters identified in Polish and English online political and social comments in posts collected between 2013 and 2018 on topics connected mainly, though not exclusively, with migration and the perception of the Other. First, the article shows that there are differences in the display and expression of emotions between English and Polish discourses, the latter being more negatively explicit and more often addressing the current online interactant. Second, in both groups, two opposing camps are identified. Finally, the rise in meaning and expressiveness of radicalization is observed in both English and Polish across the investigated period.
Transitions in Journalism—Toward a Semantic-Oriented Technological Framework

The technologies behind today’s web services, tools, and applications are evolving continually. As a result, the workflows and methods of different business sectors are undergoing constant change. The news industry and journalism are heavily affected by these changes. New technological means for practicing journalism and producing news items are being incorporated in media workflows, challenging well established journalistic norms and practices. The perpetual technological evolution of the web creates a wide range of opportunities. For this reason, both technology companies and media organizations have begun to experiment with semantic web technologies. Our focus in this paper was to discover and define the ways that semantic technologies can contribute to the technological upgrade of everyday journalism. From this perspective, we introduced the term ‘semantic journalism’ and attempted to investigate the transition of journalism to a semantic-oriented technological framework.
Design of Online and Offline Blending Teaching Mode

Facing the era of rapid development of the Internet, how to rely on information technology for online and offline blending teaching is the current upsurge in the field of information education. Through the analysis of blending classroom teaching, relying on the promotion of information technology to online and offline classroom mode, based on the design principles of paying equal attention to theory and practice, combining teaching and self-study, and parallel online and offline, this paper constructed a multi-dimensional teaching resource approach, practices online and offline, pre-class-in-class-after-class blending teaching mode, and explored the high integration of information technology and curriculum teaching to cultivate students' autonomous learning ability and increasing classroom vitality, which has certain reference value and significance for improving classroom teaching effectiveness.
Gaze window: A new gaze interface showing relevant content close to the gaze point

Abstract In this paper, we propose a novel concept of the gaze window, which follows the user's gaze to show relevant information close to their gaze point on a screen space. We explore the use of a gaze window, especially for two use cases: (1) a single‐user data entry task by displaying data‐source image close to the gaze point where the data are typed in and (2) a teleconferencing setup showing a remote partner close to the gaze point. To investigate the performance of gaze window in these cases, we conducted two experiments. For the single‐user task, we compared the gaze window with a baseline non‐gaze‐window condition and found that the gaze window significantly reduced the user's gaze movement and mental effort and increased usability. In the teleconferencing task, we compared displaying partner close to gaze point in the gaze window to displaying partner at the corner of screen, when two remote users watch a shared and synchronized content together. We found that displaying the partner's face nearby the user's gaze helped the user look at the partner more frequently, and for a longer time, significantly increasing co‐presence and emotional interdependence. As a result of this research, we also presented design guidelines for gaze‐window systems.
A method to evaluate REE-HFSE mineralised provinces by value creation potential, and an example of application: Gardar REE-HFSE province, Greenland

The rare earth elements and high-field-strength elements (REE-HFSE) exploration sector conducts most evaluations at deposit and smaller scales. It is not evident how the sector performs a preceding exploration stage—rating and prioritising REE-HFSE mineralised provinces—to determine which provinces are prospective enough to warrant investment. Here we present an objective, repeatable, low-cost method to screen any REE-HFSE province, as a foundation for district-scale investigations or asset evaluations. It is original for REE-HFSE screening, and adapted from regional scale copper, cobalt and petroleum exploration, and CO2 storage, screening methods. It is centred upon a mineralised province’s favourability for potential value creation, and to identify: (a) its main information gaps; (b) its weakest links; (c) its exploration maturity and remaining potential category; (d) how it compares against other REE-HFSE provinces; and (e) if further investigation is justified. This method incorporates geoscience, strategy, economic and socio-environmental factors in a way that is understandable and directly usable across stakeholder groups. The workflow is systematic, yet flexible enough to accommodate organisation-specific criteria, and usable for other commodities. It provides the platform to build a global REE-HFSE province map and database consistently across national boundaries and organisations. Categories for the extent of province exploration maturity and remaining mineral potential are proposed. We illustrate the applicability of these methods using the Gardar REE-HFSE Province (GRHP) of south Greenland. We conclude that it is a moderate size, frontier province that is currently of questionable favourability for value creation. To move GRHP into a positive favourability class, its current weak links need strengthening by research, government policy and industry stakeholders: evaluate the mineral system; integrate all information geospatially and place it in the public domain; help the region improve some community health and safety issues; convert some mineral resources into an Ore Reserves category; commence mining and sales production.
Infomages: Embedding Data into Thematic Images

Abstract Recent studies have indicated that visually embellished charts such as infographics have the ability to engage viewers and positively affect memorability. Fueled by these findings, researchers have proposed a variety of infographic design tools. However, these tools do not cover the entire design space. In this work, we identify a subset of infographics that we call infomages. Infomages are casual visuals of data in which a data chart is embedded into a thematic image such that the content of the image reflects the subject and the designer's interpretation of the data. Creating an effective infomage, however, can require a fair amount of design expertise and is thus out of reach for most people. In order to also afford non‐artists with the means to design convincing infomages, we first study the principled design of existing infomages and identify a set of key chart embedding techniques. Informed by these findings we build a design tool that links web‐scale image search with a set of interactive image processing tools to empower novice users with the ability to design a wide variety of infomages. As the embedding process might introduce some amount of visual distortion of the data our tool also aids users to gauge the amount of this distortion, if any. We experimentally demonstrate the usability of our tool and conclude with a discussion of infomages and our design tool.