User's Situation Research Articles

A STUDY ON THE ACTUAL USE OF SMALL-SCALE OPEN SPACES IN DENSELY BUILT-UP AREA

This report aims to clarify the actual use of small-scale open spaces in densely built-up area and element which affects its usage situation in Kyojima2,3, Sumida. We researched their usage situation and resident needs by field survey, interview, and questionnaire. As a result, resident don’t use small-scale open spaces because they are small and resident don’t have things to do at there. On the other hand, some of them are used. They are large and have facilities and events. And they are located along the main street. Consequently, size, their facilities and location affect their usage situation.

The Future Development Direction of Cloud-Associated Edge-Computing Security in the Era of 5G as Edge Intelligence

By introducing the Internet-of-Everything, new usage situations such as self-directed movement and vivid competitions constructed upon Virtual Reality or Augmented Reality expertise, besides the Industrial-Internet-of-Thing, accelerates the initial growth of edge-registering improvements. The global versatile correspondence business is now developing toward 5G. Edge processing has gotten a lot of attention around the globe as 5G is one of the major access enhancements to advance the huge scope organization of edge registration. Edge processing security has been a significant area of concern since the advent of edge registers, limiting its execution and enhancement. Edge figuring security has been greatly hampered by the innovative structures of edge-registering, the reconciliation with a huge number of innovations, the innovative usage conditions carried on through edge-processing, and common growing requirements aimed at safety insurance. This report examines the ebb and flow of examination anxiously registering security research. This article highlights the security issues of edge processing from five perspectives, including network access, key administration, protection assurance, assault mitigation, and irregularity identification, by breaking down the safety tests among edge-registering cutting-edge terms of innovative representations, and novel applications situations, as well as innovation conditions. The study separately discusses the scholastic community’s exploratory accomplishments among the applied domains, as well as the compensations for the drawbacks. In conclusion, the upcoming expansion track toward edge-computing safety has been conferred as well as projected, combining edge-cloud coordinated effort and edge intelligence.

A Refined Supervision Model of Rice Supply Chain Based on Multi-Blockchain.

With the development of Agriculture 4.0, the requirements for sustainable agriculture and precision agriculture continue to grow. As one of the three major staple foods globally, the quality and safety of rice affect human health as well as social development. To ensure the quality and safety of rice and reduce the flow of problematic rice, a multi-layer blockchain-based rice supply chain refinement supervision model MBRRSM (Multi-blockchain Rice Refined Supervision Model) is proposed from the information level. First, the characteristics of information flow in the rice supply chain are analyzed, and a classification table of key information is constructed. Second, the MBRRSM framework is designed. Based on a multi-party hybrid encryption algorithm, secure multi-party computing algorithm, multi-mode storage mechanism, and SPOP (Supervision Proof of Peers) consensus algorithm, a set of mechanisms is designed for the transmission, use, storage, and consensus of rice data in MBRRSM. Subsequently, the security and performance capabilities of MBRRSM are analyzed. Meanwhile, the SPOP consensus algorithm is analyzed. Finally, a prototype system is built based on MBRRSM and verified through exemplary scenarios in different usage situations. The results show that research on the refined supervision of the rice supply chain based on multi-blockchain can finely supervise all types of data in the rice supply chain, and provide a guarantee for enterprise users to safely transmit and use data with different privacy levels. This study presents a unique research paradigm that introduces the theories and methods of the new information field generation into the field of agricultural research, and thus assists in the strategy implementation of “holding grain in the land and storing grain in technology”.

User-Led Mental Health Service Evaluation: The Contribution of User-Focused Monitoring to Recovery-Oriented Quality Development

User-focused monitoring (UFM) is a method of user-led mental health service evaluation that focuses on strengthening user involvement and developing the quality of services. Despite an increased emphasis on user involvement and the recovery orientation of services, scientific knowledge remains limited regarding how such goals can be realised. In this study, our aim is to explore UFM with a specific focus on how recovery processes are examined through the method in order to discuss how UFM can be developed in order to support a recovery orientation in mental health service evaluation. We sampled 20 Swedish UFM reports for qualitative analysis, and we found that UFM is a promising method for integrating a personal recovery perspective in service evaluations. By being performed peer-to-peer, the method has the unique ability to gather experiential knowledge regarding the situation of service users. UFM especially contributes to exploring service users’ experiences related to social connectedness and user involvement in services. We also discuss how the method can be developed to further support a recovery orientation in UFM. This might be achieved by integrating a process-oriented approach in the evaluations and by including the user informants’ own goals and views on what constitutes meaningful support in UFM. Suggestions for future developments concern incorporating personal recovery perspectives in the training of user monitors and creating structures for aggregating the knowledge produced through UFM.

Effects of reliability indicators on usage, acceptance and preference of predictive process management decision support systems

Despite the growing availability of data, simulation technologies, and predictive analytics, it is not yet clear whether and under which conditions users will trust Decision Support Systems (DSS). DSS are designed to support users in making more informed decisions in specialized tasks through more accurate predictions and recommendations. This mixed-methods user study contributes to the research on trust calibration by analyzing the potential effects of integrated reliability indication in DSS user interfaces for process management in first-time usage situations characterized by uncertainty. Ten experts specialized in digital tools for construction were asked to test and assess two versions of a DSS in a renovation project scenario. We found that while users stated that they need full access to all information to make their own decisions, reliability indication in DSS tends to make users more willing to make preliminary decisions, with users adapting their confidence and reliance to the indicated reliability. Reliability indication in DSS also increases subjective usefulness and system reliability. Based on these findings, it is recommended that for the design of reliability indication practitioners consider displaying a combination of reliability information at several granularity levels in DSS user interfaces, including visualizations, such as a traffic light system, and to also provide explanations for the reliability information. Further research directions towards achieving trustworthy decision support in complex environments are proposed.

What’s more important for product design – usability or emotionality? An examination of influencing factors

Usability and emotionality are fundamental aspects of user experience. However, the actual creation of an equally usable and emotionally appealing product design is still challenging for product developers, not least because of competing objectives during such equal consideration of both aspects. In order to make a user-oriented decision between a more usable or more emotional product design, product developers need a profound understanding of what matters to the user in different usage situations. By conducting 22 semi-structured interviews, we contribute to this aim by identifying and examining factors that influence a user’s perceived importance of usability and emotionality in product design. In total, 29 influencing factors were identified with the purpose of use, the type of product and other people’s attitudes towards a product being most relevant for both emotionality and usability. Nine influencing factors from the literature were additionally examined in terms of their strength and direction in which they influence the importance of emotionality and usability. Hereby, considerable differences within individual expressions of the influencing factors were revealed. Furthermore, the perceived importance of emotionality varied much more than that of usability.

Enhancing Context-Aware Recommendation Using Hesitant Fuzzy Item Clustering by Stacked Autoencoder Based Smoothing Technique

Context-aware recommender systems (CARS) are a key component in businesses, notably in the e-transactions domain, since they assume that reviews, ratings, demographics, and other factors may determine customer preferences. On contrary, while evaluating the sentiment underlying the reviews and the rating score, consumers’ opinion is typically conflicting. As a result, a framework that employs either a review or a rating for top-N recommendation directs to produce unsatisfied recommendations in addition to a meager rating problem and high computation time. To overcome all the problems, a novel sentiment enhanced stacked autoencoder (SSAE) with context-specific hesitant fuzzy item hierarchical clustering (CHFHC) approach is proposed which employs online and offline phases. In the offline-phase, the meager user-item rating matrix is smoothed by learning the users’ concrete preference to a complete matrix by the SSAE approach. They are clustered offline using the CHFHC approach into context-based similar item clusters. In the online-phase, the active user gets context-based recommendations from the most similar cluster that matches the active users’ current context situation. Hence the SSAE_CHFHC approach improves the quality of Top-N recommendation corresponding to the exact contextual situation of the active user with a minimal recommendation computation time. Experiments on the (5-core) Amazon and yelp datasets proved that the intended SSAE_CHFHC framework consistently outperforms state-of-the-art recommendation algorithms on a variety of evaluation measures.

Priority-Based Resource Allocation and Energy Harvesting for WBAN Smart Health

With the emergence of new viral infections and the rapid spread of chronic diseases in recent years, the demand for integrated short-range wireless technologies is becoming a major bottleneck. Implementation of advanced medical telemonitoring and telecare systems for on-body sensors needs frequent recharging or battery replacement. This paper discusses a priority-based resource allocation scheme and smart channel assignment in a wireless body area network capable of energy harvesting. We investigate our transmission scheme in regular communication, where the access point transmits energy and command while the sensor simultaneously sends the information to the access point. A priority scheduling nonpreemptive algorithm to keep the process running for all the users to achieve the maximum reliability of access by the decision-maker or hub during critical situations of users has been proposed. During an emergency or critical situation, the process does not stop until the decision-maker or the hub takes a final decision. The objective of the proposed scheme is to get all the user processes executed with minimum average waiting time and no starvation. By allocating a higher priority to emergency and on data traffic signals such as critical and high-level signals, the proposed transmission scheme avoids inconsistent collisions. The results demonstrate that the proposed scheme significantly improves the quality of the network service in terms of data transmission for higher priority users.

Personalized Situation Adaptive Human-Vehicles-Interaction (HVI) Prediction in COVID-19 Context

The purposes are to investigate the personalized situation adaptive Human-Computer Interaction (HCI) in the COVID-19 context, achieve accurate predictions for HCI in different urban transportation situations, and solve the urban intelligent transportation problems. Problems of Human-Vehicles-Interaction (HVI) in context awareness are analyzed. Historical traffic flow in three different situations, including novice user situation, mid user situation, and expert user situation, are taken as the data sources. The HVI data are preprocessed afterward. Next, Dilated Convolution (DC) and Long-Short Term Memory (LSTM) are integrated (DC-LSTM) to build an HVI model based on situation adaptive. The proposed model is simulated to analyze its performance. Simulation experiments suggest that the Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) of the proposed model are 4.64%, 5.34%, and 7.82%, respectively. Although these three metrics increase under the mid user and expert user situations, the proposed model can still provide a higher accuracy than LTSM, Convolutional Neural Network (CNN), Simple Recurrent Network (SRN), Support Vector Regression (SVR), and Multi-Layer Perceptron (MLP). Besides, the prediction velocity can maintain about 60 Frame-Per-Second (FPS) under all three user situations. Regarding the path guidance performance, the proposed model can suppress the traffic congestion and dredge the congested sections effectively. Hence, the HVI model based on situational adaptation constructed has high prediction accuracy and traffic congestion evacuation performance, which can provide an experimental basis for the later intelligent transportation field and improving situational self-adaptability.

Who Are They and Where? Insights Into the Social and Spatial Dimensions of Imagined Audiences From a Mobile Diary Study of Twitter Users

Social media users hardly know who is reading their posts, but they form ideas about their readership. Researchers have coined the term imagined audience for the social groups that actors imagine seeing their public communication. However, social groups are not the only aspect that requires imagination: In the potentially borderless online environment, the geographical scope and locations of one’s audience are also unknown. Furthermore, research has demonstrated that imagined audiences vary between people and situations, but what explains these variations is unclear. In this article, we address these two gaps—the geographical scope and predictors of imagined audiences—using data from a mobile experience sampling method study of 105 active Twitter users from Berlin, Germany. Our results show that respondents mostly think of a geographically broad audience, which is spread out across the country or even globally. The imagined geographical scope and social groups depend on both the communicator and the usage situation. While the audience’s social composition especially depends on tweet content and respondents’ sociodemographic characteristics, the geographical scope is best explained by respondents’ biography and personal mobility, including their experience of living in other countries and local residential duration.

MALAY LANGUAGE USE AMONG UKM STUDENTS IN TERMS OF DAILY INTERACTIONS AND AFFAIRS

This study aims to look at the frequency of Malay language practice by Malay students in higher learning institutions in the aspect of interaction with people around them such as family and acquaintances as well as in public affairs. The survey involved 258 Malay students at The National University of Malaysia (UKM) who attended various undergraduate programs. The data were analysed using a percentage descriptive statistical analysis to find out the frequency value for each Malay language usage situation. The five-point Likert scale of that frequency value is marked with Each Time, Frequent, Sometimes, Rare, and Never. Data collection is done using an online questionnaire through the Google Form application. The percentage analysis recorded a value below 70% for the ‘Every Time’ frequency scale in the use of Bahasa Melayu when with friends (64.4%), when meeting new or unknown people (55.2%), during shopping at shopping malls (58.7%) and when chatting with college friends (66.5%). The results also showed that the use of language in the communication and daily affairs of Malay students at UKM is also dominated by English in certain matters, other than Bahasa Melayu. The findings of this study are expected to contribute to the planning of programs, courses and appropriate measures to inculcate the use of Bahasa Melayu among students in Malaysia.

MALAY LANGUAGE USE AMONG UKM STUDENTS IN TERMS OF DAILY INTERACTIONS AND AFFAIRS

This study aims to look at the frequency of Malay language practice by Malay students in higher learning institutions in the aspect of interaction with people around them such as family and acquaintances as well as in public affairs. The survey involved 258 Malay students at The National University of Malaysia (UKM) who attended various undergraduate programs. The data were analysed using a percentage descriptive statistical analysis to find out the frequency value for each Malay language usage situation. The five-point Likert scale of that frequency value is marked with Each Time, Frequent, Sometimes, Rare, and Never. Data collection is done using an online questionnaire through the Google Form application. The percentage analysis recorded a value below 70% for the ‘Every Time’ frequency scale in the use of Bahasa Melayu when with friends (64.4%), when meeting new or unknown people (55.2%), during shopping at shopping malls (58.7%) and when chatting with college friends (66.5%). The results also showed that the use of language in the communication and daily affairs of Malay students at UKM is also dominated by English in certain matters, other than Bahasa Melayu. The findings of this study are expected to contribute to the planning of programs, courses and appropriate measures to inculcate the use of Bahasa Melayu among students in Malaysia.

Ratemaking Model of Usage Based Insurance Based on Driving Behaviors Classification

Based on the present situation of usage based insurance (UBI) research and application, this paper puts forward the UBI rating model based on driving behavior classification, and applies the technology of data mining to the evaluation of driving behavior. The actual driving behavior data and the risk data of 400 drivers are used as experimental data. Finally, an example shows that the driving behavior classification model is superior to the driving behavior score model for the identification of accident risk, which can make UBI rate more scientific and reasonable.

Situation of food assistance users and the association with change in socioeconomic status during COVID-19 pandemic in Japan

Objective This study aimed to understand the situation of the users of food assistance activities during the COVID-19 pandemic, and to examine the relationship with the changes in socioeconomic conditions.Methods A total of 33,004 (16,065 men and 16,939 men) people aged 20 or older who cooperated with an online survey in February 2021 were included in the analysis. The analysis was conducted by classifying users of one of the following types of food assistance as food assistance users and other users as non-users: eating on site (e.g., children's cafeteria), receiving food at a specific location (e.g., food pantry), or having food delivered to their home (e.g., emergency home food delivery). A multiple logistic regression analysis was used to calculate the adjusted odds ratios (95% confidence interval (CI)) for the association between food assistance use and changes in socioeconomic status, which was assessed based on the employment status and household monthly income just before and during the COVID-19 pandemic.Results The number of users of food assistance was 3,071 (9.3%). Of these, 1,549 (4.7%) were users of children's cafeterias, 1,296 (3.9%) were users of food pantries, and 2,236 (6.8%) were users of emergency home food delivery (with duplicate responses). The adjusted odds ratio for food assistance use was 1.47 (95% CI 1.28-1.70) for those with changes in employment status compared to those with no changes. The adjusted odds ratio for food assistance use was 1.89 (1.65-2.15) for those with reduced income and 1.67 (1.37-2.03) for those with increased household income compared to those with no changes. The adjusted odds ratios for food assistance use were higher for those with changes in employment status and/or household income than those with no changes in both.Conclusions One in ten individuals used food assistance during the COVID-19 pandemic. It was suggested that many of the users of food assistance had changed their employment status or household income during the COVID-19 pandemic. In the future, it will be necessary to establish a public-private system that can provide information on local food assistance to people whose socioeconomic status has changed rapidly.

Composite Materials Based on Gelatin and Iron Oxide Nanoparticles for MRI Accuracy.

The majority of recent studies have focused on obtaining MRI materials for internal use. However, this study focuses on a straightforward method for preparing gelatin-based materials with iron oxide nanoparticles (G–Fe2O3 and G–Fe3O4) for external use. The newly obtained materials must be precisely tuned to match the requirements and usage situation because they will be in close touch with human/animal skin. The biocompatible structures formed by gelatin, tannic acid, and iron oxide nanoparticles were investigated by using FTIR spectroscopy, SEM-EDAX analysis, and contact angle methods. The physico-chemical properties were obtained by using mechanical investigations, dynamic vapor sorption analysis, and bulk magnetic determination. The size and shape of iron oxide nanoparticles dictates the magnetic behavior of the gelatin-based samples. The magnetization curves revealed a typical S-shaped superparamagnetic behavior which is evidence of improved MRI image accuracy. In addition, the MTT assay was used to demonstrate the non-toxicity of the samples, and the antibacterial test confirmed satisfactory findings for all G-based materials.

The Pursuit of Meaning and the Preference for Less Expensive Options

AbstractFinding meaning in life is a fundamental human motivation. Along with pleasure, meaning is a pillar of happiness and well-being. Yet, despite the centrality of this motive, and despite firms’ attempts to appeal to this motive, scant research has investigated how the pursuit of meaning influences consumer choice, especially in comparison to the study of pleasure. While previous perspectives would suggest that the pursuit of meaning tilts consumers toward high-quality products, we predicted and found the opposite. As compared to a pleasure or (no goal) baseline condition, six studies demonstrate that the pursuit of meaning causes people to consider how they can otherwise use their money (opportunity costs) which in turn leads to a preference for less expensive goods. This effect is robust across multiple product categories and usage situations, including both experiential and material purchases, and is obtained even when the more expensive product is perceived to deliver greater meaning. For participants pursuing meaning, making opportunity costs salient has no effect on their choices, and encouraging opportunity cost neglect increases their willingness to pay for a more expensive item. This research thus provides an initial answer as to how the pursuit of meaning shapes consumer choice processes and preferences.

Effects on Customer’s Reliability, Utilization and Purchase Intention of Using Actual Situation of Cosmetic’s Internet Shopping Mall

This study was studied to analyze significant difference of reliability of online information, utilization of internet shopping mall and cosmetic’s purchase intention of customer according to general characteristics or actual situation of usage of internet shopping mall. The 416 survey were analyzed using the statistical package (SPSS WIN 21.0). As the results, women was 73.6%, 30 age was 42.5%, final education of university was 74.8% and official worker was 32.6%. Subjects using internet of ≥5 hours per day was 22.8% and subjects showing using frequency of 1-3 times per day in cosmetic’s internet shopping mall were 37.3%. In analysis on reliability of online information, utilization of internet shopping mall and cosmetic’s purchase intention of customer according to general characteristics, reliability of online information didn’t significant difference with general characteristics but the utilization of internet shopping mall and cosmetic’s purchase intention of customer showed significant difference with general characteristics exhibiting high utilization of internet shopping mall of ≤20 age (p<0.05 and p<0.01). In analysis on reliability of online information, utilization of internet shopping mall and cosmetic’s purchase intention of customer according to actual situation of usage of internet shopping mall, reliability of online information showed significant difference with cosmetic’s purchasing price through internet during month (p<0.05). Also, utilization of internet shopping mall according to actual situation of usage of internet shopping mall showed significant difference with searching prequency and cosmetic’s purchasing rate through internet among the total cosmetic’s purchasing price. Finally, cosmetic’s purchase intention of customer according to actual situation of usage of internet shopping mall showed significant difference with internet usage per day, searching frequency of internet shopping mall, purchasing price and purchasing rate through internet shopping mall (p<0.05, p<0.01 and p<0.001). Therefore, these results will be apply cosmetic’s marketing plan.

Characterizing the spaces of consumer value experience in value co-creation and value co-destruction

Purpose This paper aims to explore how unreflective and reflective value experience emerges in value co-creation and co-destruction practices in a consumer context. Design/methodology/approach This paper presents a Heideggerian phenomenological heuristic consisting of three interrelated modes of engagement, which is used for interpretive sense-making in a dynamic and lively case context of amateur-level football (soccer) played on artificial grass. Based on a qualitative study using ethnographic techniques, this study examines the whats and the hows of value experience by individuals playing football at different qualities and in varying conditions across 25 Dutch football teams. Findings The findings reveal three interrelated yet distinct modalities of experience in value co-creation and co-destruction presented in a continuum of triplex spaces of unreflective and reflective value experience. The first is a joyful flow of unreflective value experience in emergent and undisrupted value co-creation practice with no potential for value co-destruction. Second, a semireflective value experience caused by interruptions in value co-creation has a higher potential for value co-destruction. Third, a fully reflective value experience through a completely interrupted value co-creation practice results in high-value co-destruction. Research limitations/implications This research contributes to the literature on the microfoundations of value experience and value creation by proposing a conceptual relationship between unreflective/reflective value experience and value co-creation and co-destruction mediated through interruptions in consumer usage situations. Practical implications This study’s novel perspective on this relationship offers practitioners a useful vantage point on understanding how enhanced value experience comes about in value co-creation practice and how this is linked to value co-destruction when interruptions occur. These insights help bolster alignment and prevent misalignment in resource integration and foster service strategies, designs and innovations to better influence consumer experience in journeys. Originality/value This study deploys an integral view of how consumer value experience manifests in value co-creation and co-destruction that offers conceptual, methodological and practical clarity.

Research on Furniture Design Integrating Ming-Style Furniture Modeling Elements and Image Sensor Data: Taking Suitable Old Furniture as an Example

Ming-style furniture, adhering to the excellent traditional Chinese history and culture, is the pinnacle of traditional Chinese-style furniture, which vividly embodies the cultural essence of Chinese-style furniture. However, with the current popularity of smart home products, there are many obstacles for elderly users to use smart home products. Voice interaction is one of the main interaction methods of smart home products. The design strategy of voice user interface for aging smart home products is studied to improve the experience of elderly users in operating smart home products. Based on image sensing technology, combining Ming-style furniture modeling elements, and based on context theory research, this paper proposes four types of smart home contexts for elderly users, including user context, task context, time context, and environmental context, so as to propose a specific smart home product voice user interface design strategy. According to the user’s situational characteristics, a multichannel interaction design of voice user interface is proposed, an emotional and personalized voice user interface is constructed, and a design strategy of context memory assisting the dialogue process is constructed. According to the task, time, and environmental situation of elderly users, it proposes design strategies such as active interactive voice user interface design and provides continuous behavioral service experience. Conclusion. The research results provide a method and strategy reference for the design and development of the voice user interface of smart home products and provide a more natural and comfortable experience of using smart home products for elderly users.

Healthcare Big Data Privacy Protection Model Based on Risk-Adaptive Access Control

Edge computing is playing an increasingly important role in the field of health care. Edge computing provides high-quality personalized services to patients based on user and device data information. However, edge nodes will collect a large amount of sensitive patient information, and patients will also bear the risk of privacy disclosure while enjoying personalized services. How to reduce the risk of privacy disclosure while ensuring that patients enjoy personalized services brought by edge computing is the research content of this paper. In this paper, the work flow and management mode of Hospital Information System (HIS) are investigated on the spot, and the risk-adaptive access control model based on entropy is established. First, we use International Classification of Diseases, Tenth Revision (ICD-10) to mark the information resources accessed by users and use information entropy to measure the correlation “α” between medical information accessed by users and work tasks. Finally, we analyze the relationship between correlation “α” and risk through an example. The results show that users with high correlation α have low risk of access behavior, and users with low risk have high correlation α of access information resources and work goals. This discovery can help managers predict users’ access behavior in the Big Data environment, so as to dynamically formulate access control policies according to the actual access situation of users and then realize the privacy protection of medical big health data.