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Ever since Mark Weiser coined the term “ubiquitous computing” (ubicomp) in 1988, there has been a general interest in proposing various solutions that would support his vision. However, attacks targeting devices and services of a ubicomp environment have demonstrated not only different privacy issues, but also a risk of endangering user’s life (e.g. by modifying medical sensor readings). Thus, the aim of this paper is to provide a comprehensive overview of security challenges of ubicomp environments and the corresponding countermeasures proposed over the past decade.

The results of this paper are based on a literature review method originally used in evidence-based medicine called systematic literature review (SLR), which identifies, filters, classifies and summarizes the findings.

Starting from the bibliometric results that clearly show an increasing interest in the topic of ubicomp security worldwide, the findings reveal specific types of attacks and vulnerabilities that have motivated the research over the past decade. This review describes most commonly proposed countermeasures – context-aware access control and authentication mechanisms, cryptographic protocols that account for device’s resource constraints, privacy-preserving mechanisms, and trust mechanisms for wireless ad hoc and sensor networks.

To the best of our knowledge, this is the first SLR on security challenges in ubicomp. The findings should serve as a reference to an extensive list of scientific contributions, as well as a guiding point for the researchers’ novel to the security research in ubicomp.

This study aims to automate the process of converting grading patterns into parametric patterns using artificial intelligence and to objectively evaluate the fitness of the converted patterns.

The developed system consists of a user interface that defines input data by importing multi-size grading patterns, an artificial neural network that learns the relationship between human body size and pattern geometry, and a module that converts training results into parametric patterns. In order to evaluate the fitness of the generated pattern, an objective fitting evaluation method using drape simulation was developed.

The body sizes of the wearer were input to the converted parametric pattern to generate a customized pattern. Resulting pattern showed a better fit than the grading pattern on the off-average body model.

In this study, a method has been developed that enables the users with minimal pattern drafting knowledge to convert grading patterns into parametric patterns using artificial intelligence and drape simulation. The human body's symmetry and the physical properties of fabric were not considered.

The system developed in this study requires less data compared to existing methods that attempt to design clothing patterns with machine learning. In addition, it was possible to evaluate pattern fitness on various body models through drape simulation based fit evaluation process for the first time.

The coronavirus disease 2019 (COVID-19) pandemic caused significant disruption to the global labor market, resulting in a rapid transition toward remote work, e-commerce and workforce automation. This shift has sparked a considerable amount of public discussion. This study aims to explore the online public's sentiment toward remote work amid the pandemic.

Based on justice theory, this paper examines user-generated content on social media platforms, particularly Twitter, to gain insight into public opinion and discourse surrounding remote work during the COVID-19 pandemic. Employing content analysis techniques such as sentiment analysis, text clustering and evolutionary analysis, this study aims to identify prevalent topics, temporal patterns and instances of sentiment polarization in tweets.

Results show that people with positive opinions focus mainly on personal interests, while others focus on the interests of the company and society; people's subjectivities are higher when they express extremely negative or extremely positive emotions. Distributive justice and interactional justice are distinguishable with a high degree of differentiation in the cluster map.

Previous research has inadequately addressed public apprehensions about remote work during emergencies, particularly from a justice-based perspective. This study seeks to fill this gap by examining how justice theory can shed light on the public's views regarding corporate policy-making during emergencies. The results of this study provide valuable insights and guidance for managing public opinion during such events.

Traditional laboratory measurements of soil water diffusivity (D) and soil water retention curve (SWRC) are always time-consuming and labor-intensive. Therefore, this paper aims to present a simple and robust test method for determining D and SWRC without reducing accuracy.

In this study, a D model of unsaturated soil was established based on Gardner–Russo model and then a combination of Gardner–Russo model with one-dimensional horizontal absorption method to obtain n and a parameters of Gardner–Russo model. One-dimensional horizontal absorption experiments on loam, silt loam and sandy clay loam were conducted to obtain the relationships between measured infiltration rate and cumulative infiltration with wetting front distance. Based on the obtained relationships, the measured infiltration data from the one-dimensional horizontal absorption tests were used to calculate n and a parameters and further constructing D and SWRC.

Both the calculated D and SWRC inversed from the infiltration data were in good agreement with the measured ones that obtained from the traditional horizontal absorption method and the centrifuge method, respectively. Error analysis indicated that only the infiltration data are enough to reliably synchronously determine D and SWRC.

A simple and robust method is proposed for synchronous determination of soil water diffusivity and water retention curve.

COVID-19, an infectious disease first identified in China, has resulted in an ongoing pandemic all over the world. Most of the countries have been experiencing a difficult period during the fighting of this pandemic. The purpose of this study is to explore the effect of privacy concerns and cultural differences on public opinion related to the pandemic. The authors conducted a comparative analysis of public opinion in the US and in China as a case study, in order to determine the results.

National policies on important issues faced during the COVID-19 pandemic in the US and in China were examined through a comparative analysis. The authors used text clustering and visualization to mine public opinion on two popular social media platforms, Twitter and Weibo. From the perspectives of concern for privacy and of national culture, this study combines qualitative and quantitative analysis to discover the acceptance level of national policies by the public in the two countries.

The anti-pandemic policies and measures of the US and China reflect the different characteristics of their respective political systems and national cultures. When considering the culture of the US, it is hard to establish and enforce a rigorous regulation on either mask wearing in public or home quarantine on the national level. The opinions of US people are diverse, regarding national COVID-19 policies, but they are rather unified on privacy issues. On the other hand, Chinese people show a high acceptance of national policies based on their mask-wearing customs and their culture of collectivism.

Prior studies have paid insufficient attention to the ways in which user privacy and cultural difference affect public opinion on national policies between the US and China. This case study that compares public opinion on current and topical issues which are closely bound up with public life shows originality, as it innovatively provides a cross-cultural perspective on the research of public opinion dissemination during emergencies by considering the ongoing COVID-19 pandemic.

The purpose of this study is to examine characteristics of retracted publications from Indian authors and inspect a relationship between journal impact factor (JIF) and the number of authors (NoA).

The authors examined the general characteristics of retracted publications and investigated the correlation between JIF and NoA from Indian authors from January 1, 2017, to December 31, 2022. Data were mined from retraction watch http://retractiondatabase.org/ (n = 1,459) and determined the year of publication, year of retraction, authors, journals, publishers and causes of the retractions. A journal citation report was extracted to gather the JIFs.

About one-third of retracted papers were published in 2020; 2022 has the highest retraction rate (723); studies with two authors represent about one-third (476) of the published articles; Journal of Ambient Intelligence and Humanized Computing (354) has the highest number of retractions; Springer published the most retracted papers (674); and the majority of the journal (1,133) is indexed in journal citation reports, with impact factor extending from 0.504 to 43.474. Retraction due to legal reasons/legal threats was the most predominant reason for retraction.

This study reflects growth in author collaborations with a surge in the JIF. This study recommends that quick retraction is essential to reduce the adverse effects of faulty research.

The purpose of this paper is to investigate the effect of welding procedure on the corrosion behaviors of weathering steel 09CuPCrNi in marine atmospheric environment. The corrosion processes of weathering steel 09CuPCrNi and its welded joints in marine atmospheric environment were simulated by a salt spray dry-wet test.

The corrosion behaviors of the base metal and the welded joints at corrosion times of 2, 4, 8, 12, 24 weeks were investigated by weight loss test, electrochemical techniques, scanning electron microscope (SEM) and electron probe micro-analyzer (EPMA). The corrosion rates, as well as the morphologies and electrochemical characteristics of corrosion products, the distribution of major alloying elements in rust layer were obtained. The influence of welding on the atmospheric corrosion of 09CuPCrNi was studied.

The results indicate that the corrosion rate of the 09CuPCrNi welded joints decreases gradually with the corrosion time, and the major alloying elements are enriched in the inner rust layer, which are similar to that of the base metal. In the early stage during the corrosion process, the welded joints with inhomogeneous structure show the poorer corrosion resistance than that of the base metal. However, it looks the opposite way around in the late corrosion stage, when the uniform corrosion products with even thickness of the base metal tend to detach from the substrate easier and earlier and resulting in cracks, which increase the corrosion rate comparatively with that of the welded joints.

09CuPCrNi low alloy steel is a kind of typical weathering steel developed in China which is similar to Corten A developed by USA. Nowadays, 09CuPCrNi low alloy steel is widely adopted in many fields which require welding processes. In the past years, the research of weathering steel welded joints was mainly concentrated on the strength, toughness and weldability. Less work has been done to investigate the difference of corrosion evolution and characteristics between the base metal and its welded joints. Thus, the main objective of the present work was to analyze the influence of welding on the atmospheric corrosion.

It is suggested that, to be successful, innovation teams should be small and consist of people with key expertise who want to participate and develop new solutions within their organisations. When it comes to conducting innovation work, I suggest shared leadership may be a factor influencing success. In this chapter, a theoretical framework is presented on the shared leadership of innovation teams. The key to establishing shared leadership in innovation teams is to plan for it as the team is created, not after the team has already been formed, as this may result in various problems in the intended innovation project. The proposed framework details key aspects to consider; some of which are related to external factors such as management and resources, and some to internal factors such as the team’s size, competencies, and their ability to develop norms and ways of working together. The proposed framework is applicable for managers, innovation leaders, and team members, and contributes to previous research on shared leadership and innovation leadership. Further research on the proposed framework is suggested.

The global prevalence of social media and its potential to cause polarization are highly debated and impactful. The previous literature often assumes that the ideological bias of any media outlet remains static and exogenous to the polarization process. By studying polarization as a whole from an ecosystem approach, the authors aim to identify policies and strategies that can help mitigate the adverse effects of polarization and promote healthier online discourse.

To investigate online polarization, the authors perform a systematic review and analysis of approximately 400 research articles to explore the connection between cognitive bias and polarization, examining both causal and correlational evidence. The authors extensively evaluate and integrate existing research related to the correlation between online polarization and crucial factors such as public engagement, selective exposure and political democracy. From doing so, the authors then develop a PolarSphere ecosystem that captures and illustrates the process of online polarization formation.

The authors' review uncovers a wide range of associations, including ideological cognition, bias, public participation, misinformation and miscommunication, political democracy, echo chambers and selective exposure, heterogeneity and trust. Although the impact of bias on social media polarization depends on specific environments and internal/external conditions, certain variables exhibit strong associations across multiple contexts. The authors use these observations as a basis from which to construct PolarSphere, an ecosystem of bias-based polarization on social media, to theorize the process of polarization formation.

Based on the PolarSphere ecosystem, the authors argue that it is crucial for governments and civil societies to maintain vigilance and invest in further research to gain a deep comprehension of how cognitive bias affects online polarization, which could lead to ways to eliminate polarization.