User Context Research Articles

Effects of cannabis legalisation on patterns of cannabis consumption among adolescents in Ontario, Canada (2001-2019).

Cannabis legalisation was enacted on 17 October 2018 in Canada. Accordingly, the effects of cannabis legalisation on patterns of cannabis consumption were examined among adolescents, including on cannabis initiation, any cannabis use, daily cannabis use and cannabis dependence. Data from a biennial population-based, cross-sectional survey of students in Ontario were pooled in a pre-post design (2001-2019; N = 89,238). Participants provided self-reports of cannabis initiation, any cannabis use, daily cannabis use and cannabis dependence. Long-term trends in these patterns of cannabis consumption over two decades of observation were characterised to provide a broader context of usage. The effects of cannabis legalisation on patterns of cannabis consumption were quantified using logistic regression analyses. Long-term trends over the two decades of observation indicated that cannabis initiation decreased and then increased (p = 0.0220), any cannabis use decreased and daily cannabis use decreased (p < 0.0001 and p = 0.0001, respectively) and cannabis dependence remained unchanged (p = 0.1187). However, in comparisons between the pre-cannabis legalisation period (2001-2017) and the post-cannabis legalisation period (2019), cannabis legalisation was not associated with cannabis initiation (odds ratio; 95% confidence interval 1.00; 0.79-1.27), but it was associated with an increased likelihood of any cannabis use (1.31; 1.12-1.53), daily cannabis use (1.40; 1.09-1.80) and cannabis dependence (1.98; 1.29-3.04). Cannabis legalisation was not associated with cannabis initiation, but it was associated with an increased likelihood of any cannabis use, daily cannabis use and cannabis dependence.

Sequence recommendation using multi-level self-attention network with gated spiking neural P systems

Sequence recommendation is used to predict the user's next potentially interesting items and behaviors. It not only focuses on the user's independent interaction behavior, but also considers the user's historical behavior sequence. However, sequence recommendation still faces some challenges: the existing models still have shortcomings in addressing long-term dependencies and fully utilizing contextual information in sequence recommendation. To address these challenges, we propose a four-channel model based on a multi-level self-attention network with gated spiking neural P (GSNP) systems, termed SR-MAG model. The four channels are divided into two groups, and each group is composed of an attention channel and an GSNP attention channel. Moreover, they process long-term sequences and short-term sequences respectively to obtain long-term or short-term attention channel features. These features are then passed through a self-attention network to effectively extract user context information. The proposed SR-MAG model is tested on three real datasets and compared with 10 baseline methods. Experimental results demonstrate the effectiveness of the proposed SR-MAG model in sequence recommendation tasks.

Farming-as-a-service initiative in the making: Insights from emerging proto-practices in Sweden

This paper focus on the emergence of farming-as-a-service initiatives that combines ideas about controlled environment agriculture with digital technologies to produce food in cities. These initiatives are founded upon the view that it can secure local food provision while reducing the environmental impacts of food systems. While there are promising value claims surrounding such initiatives, knowledge about their actual effects is limited. This paper begins to address this research gap by investigating the early uptake of such practices in user context. Exploratory case study research was conducted focusing on the emergence of farming-as-a-service initiatives in Sweden. Drawing on practice theory of innovation, it explores the implementation of digitally augmented and service-oriented farming practices in user contexts. The findings shows that its implementation follows a transformational alignment process where new practices detach or attach to existing flows of practices. While new practices of service-oriented farming are fluid and unstable in relation to established practices, they hold transformative potential. Thus, our study contributes with an in-depth understanding of the implementation of farming-as-a-service and highlight potential implication for further uptake of such practices.

The Impact of Applying English Chats of Whatsapp Application on Students’ English Vocabulary Mastery

This study aims to determine the impact of applying English chat on students' English vocabulary mastery through the WhatsApp application. It employs a qualitative research method with a qualitative descriptive design involving 10 students. Data collection techniques include observation, interviews, and documentation. The study reveals several impacts on students' English vocabulary mastery as a result of using English chats on WhatsApp, including improvements in word meaning, contextual usage, spelling, pronunciation, and understanding of word forms. However, there is a noted limitation regarding pronunciation development due to the nature of WhatsApp as a communication application, suggesting that face-to-face learning may be more effective in this aspect. Students perceive the impact of using English chats on WhatsApp positively, as they enjoy the learning experience and find teachers responsive to their questions. WhatsApp is regarded as a user-friendly application with potential educational benefits, accessible anytime and anywhere.Keywords—Vocabulary, Impact of English Chat, WhatsApp

An empirical evaluation of the predictors and consequences of social media health-misinformation seeking behavior during the COVID-19 pandemic

PurposeDrawing upon social cognitive theory, this study aims to investigate the potential predictors and consequences of social media health-misinformation seeking behavior during the coronavirus (COVID-19) pandemic.Design/methodology/approachUsing a sample of 230 international students studying at Wuhan University and Beijing Language and Cultural University, China, this study employs structural equation modeling to analyze the collected data.FindingsThe results indicate that personal factors such as lack of health information literacy, environmental factors, information overload and social media peer influence have a significant effect on behavior, namely social media health-misinformation seeking behavior, which further influences outcomes, namely social media users' anxiety during the COVID-19 pandemic. In addition, both lack of health information literacy and social media peer influence have significant and direct effects on social media users' anxiety. However, the direct effect of information overload on social media users' anxiety is insignificant.Originality/valueFirst, this study contributes to the literature on the individuals' social media health-misinformation seeking behavior, its precursors and its consequences, specifically on their mental healthcare during a pandemic situation. Second, this research is one of the pioneer studies that extend social cognitive theory to the context of social media health-misinformation seeking behavior and users' anxiety relationship.

Phishing like the first step to gaining access

Phishing as a term that means the technique of sending phishing messages will be re-searched based on findings in public access and using the listed links. The process of a phish-ing attack will be analyzed, and then we will pay attention to the technical vectors of how us-ers become victims of the attack. Finally, existing research on phishing attacks and related prevention approaches will be reviewed. Mitigating phishing attacks is an important research topic worth exploring. Although a lot of research has been done, this threat still exists in the real world, and its prevalence is constantly increasing. According to research results, detecting phishing attacks is a difficult problem. There are two main strategies used to mitigate phishing attacks; or improving the performance of phishing detection technology or improving people's awareness of these at-tacks. Developing human expertise is a key way to defeat phishing attacks, as phishing attacks exploit human weaknesses rather than network weaknesses. Also, humans are always the weakest link in social engineering attacks. Compared to phishing website detection, phishing email detection may require user in-volvement to achieve better detection results. Because the success of a phishing email de-pends on its context. Specifically, when the premise of the phishing email is consistent with the user's work context (or current situation). Most anti-phishing solutions are implemented to mitigate general phishing attacks, but they ignore some specific situations, such as advanced phishing attacks. To prevent advanced phishing attacks, phishing websites are difficult to detect if a victim is attacked using stolen DNS data because the URL content and website content are the same as legitimate websites. Most content-based approaches may not work because the content of the accessed URL is an important factor in the decision. To prevent subdomain hijacking attacks, it is difficult to detect a phishing website if the phishers have hosted the website on a subdomain taken from a legitimate website. Regardless of the web content, URL, and SSL certificate information, they will all be the same as the le-gitimate website. Moreover, the approach to enumeration of subdomains needs improvement, as most current tools are based on rough enumeration, existing dictionaries may not cover all instances of subdomains, as some subdomains may be meaningless.

A Novel Approach of Reducing Energy Consumption by utilizing Big Data analysis in Mobile Cloud Computing

With the rapid proliferation of smart mobile devices and increasing adoption of cloud computing services, energy efficiency has become an important issue in mobile cloud environments. High energy consumption not only results in higher operational costs but also creates sustainability concerns related to cloud infrastructure and services. This paper proposes leveraging big data techniques such as machine learning and predictive analytics to optimize resource allocation and reduce energy consumption in mobile cloud computing. The massive amount of data on factors like user behavior, mobility patterns, network availability, and resource utilization can provide key insights to improve energy efficiency. We present an intelligent predictive framework to forecast mobile cloud resource demands and enable dynamic scaling of cloud configurations aligned to current needs. By proactively adapting cloud resources based on learned models and detected usage patterns, over-provisioning and under-utilization can be minimized. Specifically, we demonstrate how clustering, classification, regression, and times series models derived from contextual usage data can significantly improve energy efficiency when integrated with mobile cloud management systems. The proposed approaches are validated experimentally using simulated workloads and real-world trajectory data sets. Results indicate average energy savings of 42% and up to 62% for certain user groups compared to conventional cloud resource allocation techniques. This work provides an important contribution toward building more sustainable and energy efficient mobile cloud computing systems to meet the mobility and computing demands of the future through the transformative power of big data analytics.&#x0D;

Exploring the Impact of Self-Concept and IT Identity on Social Media Influencers’ Behavior: A Focus on Young Adult Technology Features Utilization

This research investigates the inspiration of self-concept and Information Technology (IT) identity on the behavior of Social Media Influencers (SMI), specifically regarding their utilization of technology features. With the advent of social media, individuals have been presented with a unique opportunity to showcase their creativity and connect with a broader audience, known as “followers.” Drawing upon the unified theory of acceptance and use of technology (UTAUT), this study examines the relationship between SMIs behavior in utilizing technology features, self-concept, and IT identity within the context of social media platform usage. The research methodology employed in this study is partial least squares (PLS) regression, providing a comprehensive understanding of how individuals’ self-concept shapes their IT identity concerning the usage of social media platform features. The findings of this study have significant implications for businesses seeking to engage with SMIs and individuals aiming to establish their presence on social media. The research highlights TikTok’s potential as a platform for self-expression and personal brand development, underscoring the importance of self-concept and IT identity in the realm of SMIs.

Characterizing information access needs in gaze-adaptive augmented reality interfaces: implications for fast-paced and dynamic usage contexts

ABSTRACT Gaze-adaptive interfaces can enable intuitive hands-free augmented reality (AR) interaction but unintentional selection (i.e. “Midas Touch”) can have serious consequences during high-stakes real-world AR use. In the present study, we assessed how simulated gaze-adaptive AR interfaces, implementing single and dual gaze inputs, influence Soldiers’ human performance and user experience (UX) in a fast-paced virtual reality marksmanship task. In Experiment 1, we investigated 1- and 2-stage dwell-based interfaces, finding confirmatory dual gaze dwell input effectively reduced Midas Touch but also reduced task performance and UX compared to an always-on (AO) interface. In Experiment 2, we investigated gaze depth-based interfaces, finding similar negative impacts of confirmatory dwell on Midas Touch, task performance, and UX. Overall, compared to the AO interface, single gaze input interfaces (e.g. single dwell or gaze depth threshold) reduced viewing of task-irrelevant information and yielded similar task performance and UX despite being prone to Midas Touch. Broadly, our findings demonstrate that AR users performing fast-paced dynamic tasks can tolerate some unintentional activation of AR displays if reliable and rapid information access is maintained and point to the need to develop and refine gaze depth estimation algorithms and novel gaze depth-based interfaces that provide rapid access to AR display content.

Evaluating the Usability of a Gaze-Adaptive Approach for Identifying and Comparing Raster Values between Multilayers

Raster maps provide intuitive visualizations of remote sensing data representing various phenomena on the Earth’s surface. Reading raster maps with intricate information requires a high cognitive workload, especially when it is necessary to identify and compare values between multiple layers. In traditional methods, users need to repeatedly move their mouse and switch their visual focus between the map content and legend to interpret various grid value meanings. Such methods are ineffective and may lead to the loss of visual context for users. In this research, we aim to explore the potential benefits and drawbacks of gaze-adaptive interactions when interpreting raster maps. We focus on the usability of the use of low-cost eye trackers on gaze-based interactions. We designed two gaze-adaptive methods, gaze fixed and gaze dynamic adaptations, for identifying and comparing raster values between multilayers. In both methods, the grid content of different layers is adaptively adjusted depending on the user’s visual focus. We then conducted a user experiment by comparing such adaptation methods with a mouse dynamic adaptation method and a traditional method. Thirty-one participants (n = 31) were asked to complete a series of single-layer identification and multilayer comparison tasks. The results indicated that although gaze interaction with adaptive legends confused participants in single-layer identification, it improved multilayer comparison efficiency and effectiveness. The gaze-adaptive approach was well received by the participants overall, but was also perceived to be distracting and insensitive. By analyzing the participants’ eye movement data, we found that different methods exhibited significant differences in visual behaviors. The results are helpful for gaze-driven adaptation research in (geo)visualization in the future.

Shades of the Assessment of Slavic Loanwords in Southern Aukštaitian Subdialects

The article discusses the connotation, context of usage and tendencies of loanwords (nouns and adjectives) from Slavic languages used in the subdialects of the Southern Aukštaitians. The research conducted revealed that the constant connotation is usually characteristic of loanwords that name persons and other living beings by their character traits, habits and inclinations, less often by their physical characteristics. Loanwords acquire a contextual connotation in contexts (combinations of words and sentences) in which the physical characteristics and appearance of the object under discussion (a person or other living being) are assessed from a certain aspect. The positive or negative shade of the assessment of loanwords with constant connotation can be used not only in a word taken separately but also in a wider context of usage. Loanwords of Southern Aukštaitian subdialects usually have a negative connotation. The spectrum of the assessment of the object in question is quite wide: from teasing to ridicule or even bullyin. Loanwords in certain contexts are used as having a greater emotional expression than Standard language words.

Military slang: Origin, structure and semantics

The humankind has been facing different wars and military conflicts during its existence and development. In the current globalized world, the role of the military is very essential and obvious. Furthermore, military slang in English is of utmost significance due to the leading role of the military from various English-speaking countries. The aim of the following research is to identify and analyze military slangy words and phrases in English; to create the military slang phrases and words corpus; to make their semantic and structural characteristics analyses; and to explain their practical usage context. The methods applied in this research include linguistic analysis, which was utilized in the selection of military slang words and phrases applied in modern English; the word-building analysis, which helped in determining semantics and structural features of military words and phrases utilized in the English language; and linguo-cultural and socio-cultural analyses that allowed giving explanations of the UK and US military traditions, cultures, and vocabulary specific features. The specific characteristics of military slang are dynamism, exaggerated expression, broad usage by the military, and general familiarity. The military slang vocabulary units have the same formation ways typical of general English vocabulary, including meanings transfer (metaphor), abbreviation and acronyms, blending, affixation, conversion, shortening, and compounding.

Problem-Based Learning Model to Improve English Learning Achievement

Examining the language components, textual organization, and social function of statements that provide services and answers based on usage context is one of the most challenging assignments for students. It is necessary to find a remedy because student achievement data from recent years indicates that they are quite poor when it comes to studying this content. Thus, 32 students from class XI MA As'diyah Putri Sengkang served as subjects for a classroom action study that was conducted. English learning achievement is the subject of the study. Determining and assessing the PBL model's efficacy in raising English learning outcomes is the goal of this study. Utilizing learning accomplishment exams, data was gathered and subjected to both qualitative and descriptive analysis. If this action research attains a minimum average score of 75 and a minimum of 82% for classical learning completeness, it is considered effective. According to the study findings, cycle I had an average score of 72.21 and 75.64% for classical completeness. In cycle II, on the other hand, classical completeness reached 92.48%, and the average score was 74.32. In the second semester of the 2022-2023 academic year, the class XI MA As'adiyah Putri Sengkang students can attain better learning outcomes by implementing the PBL learning model in two cycles.

Analysis of the Usage Context of an mHealth Application for Equestrians.

One possibility to support veterinarians in times of a vet shortage is by providing animal owners with a technical decision support for deciding whether their animal needs to be seen by a vet. As the first step in the user-centered development of such an mHealth application for equestrians, an analysis of the context of use was done. The analysis was carried out by reviewing existing literature and conducting an online survey with 100 participants. Characteristics of the user group and the usage context are presented using an adaptation of the four layers of diversity. Many equestrians are lacking health-related knowledge and competencies as well as social networks supporting them in decision making and gaining further information. This may apply to owners of other animal species in broad ranges as well. The results of the analysis provide information to software developers and researchers on mHealth applications for pet owners in general and equestrians in particular to focus their work on the users' needs and therefore provide efficient results/software.

The Loop and Reasons to Break It: Investigating Infinite Scrolling Behaviour in Social Media Applications and Reasons to Stop

Today's social media (SM) platforms are toolkits consisting of features with different use cases, some strongly related to habitual and regretful use. Especially Infinite Scrolling (IS) has been reported to make users feel like they are being caught in a loop, regretfully elongating SM sessions. We investigated and defined this loop while unveiling the processes that make users break it. Based on a one-week-long field study (N=46), we unfolded and categorized general reasons for leaving social media and related those to IS. In light of our findings, we argue that SM interventions should not only focus on the app but incorporate the user's context, as most reasons to break SM sessions were not related to the app but the user's general context. Our findings and prior work also indicate the coexistence of multiple loops, which we define as inner (intra-session) loops surrounded by an outer (habitual) loop.

A Mobile Augmented Reality App for Creating, Controlling, Recommending Automations in Smart Homes

Automations in the context of smart homes have been adopted more and more frequently; thus, users should be able to control them and create automations most suitable to their needs. Current solutions for this purpose are based on visual apps with conceptual representations of possible automation elements. However, they tend to be static, abstract, and detached from the user's real context. In this paper, we propose a novel solution based on mobile augmented reality, which provides situated, dynamic representations associated with the physical objects available in the current users' context while they are freely moving about. It allows direct interaction with the objects of interest, monitoring nearby objects' automations while moving, and creating new automations or modifying existing ones. It also supports users with recommendations of object and service configurations relevant to complete the editing of the new automations. The paper also reports on a user test, which provided positive feedback.

The Use of Engghi-Bhunten Speaking Levels by Madurese Students in Al-Azhar Islamic Boarding School: A Sociolinguistic Study

The speech level of èngghi-bhunten holds significant importance within the broader context of the ML and culture. It refers to a distinct level of speech that reflects cultural values, social norms, and a rich historical layer. This study examines the form, function, factors, and the context of using the ML èngghi-bhunten at the Al-Azhar Islamic Boarding School Situbondo. This research is a type of qualitative research. The method of data collection is in the form of an observation method. The observations carried out included the listening-engagement technique, the free listening-engagement technique, supported by recording and note-taking techniques and supplemented by the interview method. The observation method was employed to observe the use of èngghi-bhunten speech level at Al-Azhar Islamic Boarding School. The researcher recorded social interactions, usage contexts, and the underlying factors behind the use of èngghi-bhunten. Besides, semi-structured interviews were conducted with Madurese students (santri) who possessed knowledge about the usage of èngghi-bhunten. Through these interviews, the researcher gained a deeper understanding of the perceptions, meanings, and contexts surrounding the use of èngghi-bhunten. The collected data were then written in the form of orthographic writing. The analytical method used in this research is contextual analysis, namely the analysis method applied to the data by basing, calculating, and linking the context which is a means of clarifying an intention in the form of a situation related to an event. The results showed that (1) the èngghi-bhunten only used in the dhelem family (Kiai and Nyai); (2) santri always use ML èngghi-bhunten to Kiai and Nyai as a reflection of the Salaf pesantren and as a form of polite manners.

Context Matters: Understanding the Effect of Usage Contexts on Users’ Modality Selection in Multimodal Systems

Users often select different modalities in multimodal systems based on context and function. This study aimed to investigate the impact of context on users’ modality selection in a multimodal system. A modality selection task was presented through the developed multimodal system, where the task’s difficulty was controlled based on the number of syllables and touches. The experiments were examined in four usage contexts (baseline, watching, reading, and driving), and the selected modality, physical and mental effort, and satisfaction were measured. A regression model for predicting modality selection was established using binomial logistic regression. The results showed that voice usage increased in the order of baseline, watching, reading, and driving contexts. It was revealed that these changes were attributable to differences in physical and mental interaction efforts of modalities according to contexts. Our finding provides valuable insights into users’ modality selection in different contexts, which could inform the design of more efficient multimodal systems.

Semantic micro-dynamics as a reflex of occurrence frequency: a semantic networks approach

Abstract This article correlates fine-grained semantic variability and change with measures of occurrence frequency to investigate whether a word’s degree of semantic change is sensitive to how often it is used. We show that this sensitivity can be detected within a short time span (i.e., 20 years), basing our analysis on a large corpus of German allowing for a high temporal resolution (i.e., per month). We measure semantic variability and change with the help of local semantic networks, combining elements of deep learning methodology and graph theory. Our micro-scale analysis complements previous macro-scale studies from the field of natural language processing, corroborating the finding that high token frequency has a negative effect on the degree of semantic change in a lexical item. We relate this relationship to the role of exemplars for establishing form–function pairings between words and their habitual usage contexts.

Investigating Themes That Are Embedded in Dagaaba Proverbs

A plethora of literature exist about proverbs in general and Dagaaba proverbs in particular but, little is said about the themes that are embedded in them with particular reference to the central dialect of Dagaare. It is very important to note that, the central dialect or otherwise the standard dialect of Dagaare is used for academic and examination purposes. This paper therefore seeks to investigate the concept and functions of proverbs and critically examine the themes that are embedded in Dagaaba proverbs. The functions of proverbs are put into two; didactic and aesthetic. The themes have been clearly explained in the work. A purposive sampling technique was implemented and the design of the research was qualitative. The research framework was content analysis since the data analysis was mainly descriptive. The sample population for the study was focused on three (3) language communities in Ulkpong Traditional area of the Upper West Region of Ghana. The instruments used for data collection were unstructured interview and participatory observation. Eight themes were identified in the proverbs. The theme of patience and perseverance, appreciation, unity, laziness, indiscipline, ignorance, hard work and greed were chosen because of their importance to human and national development. Proverbs are general seen as a cultural heritage, which is held in high regard since it is generally believed that the philosophy, value system, wisdom and knowledge of the society are embedded in them. The findings confirmed that Dagaaba proverbs have various themes as far as their contextual usage is concerned.