User Benefits Research Articles

A survey on cross-media search based on user intention understanding in social networks

With the increasing popularity of online social networks, more and more people are posting information, updating their statuses, and searching for topics there. Massive cross-media big data has been gathered by online social networks, with high dynamics, context-sparsity, and cross-media semantic gaps. In addition, it can be challenging to understand users' search intentions in the setting of social networks. The above problems have brought severe challenges and obstacles to cross-media searches, which also attracted more and more attention on social networks. As a relatively new research topic and interest, the concept, methodology, and overall research idea of cross-media search based on user search intention understanding are not evident in the literature. The research also lacks a unified paradigm and relatively complete research ideas on social networks. To solve these problems, we reviewed more than 100 references based on our preliminary exploration and research experience in this field from the whole process involved. We also detailed methodology, datasets, evaluation indicators, experiment evaluation, and research trends and analyzed the challenges. These works will help beginners quickly establish research ideas and processes in this field, and enable them to focus on algorithm design without paying too much attention to datasets, evaluation metrics, and research frameworks. We believe this review will attract more researchers to focus on social network cross-media search based on user search intention understanding and benefit their work.

RESAT: A Utility-Aware Incentive Mechanism-Based Distributed Spatial Cloaking

Distributed spatial cloaking (DSC) enables users to enjoy precise location-based service (LBS) with location privacy preserving. An incentive mechanism is necessary to encourage users to cooperate. However, due to the inappropriate design of incentive mechanisms, the existing works cause low user benefits and fail to encourage users, ruining the expected incentive effect. Moreover, introducing a third party to manage users’ information also causes the existing works to disclose users’ privacy and be unpractical. To address these issues, we propose a utility-aware incentive mechanism-based distributed spatial cloaking (RESAT). By the idea of utility theory and optimization theory, RESAT devises basic and extended incentive mechanisms. The two mechanisms for assuming that all users are honest and that malicious users provide unreasonable locations. RESAT proposes an incentive mechanism-based cloaking cooperation without a third party, incorporating the developed mechanisms based on the blind signature. Theoretical analysis indicates that RESAT achieves incentive compatibility and is secure. Extensive experiments on the real data set show that compared with the existing works, RESAT enables 1 time more users to cooperate at best while eliminating the malicious behaviors that provide unreasonable locations. The required DSC construction time delay is limited.

Gender Differences in Perceived Barriers and Benefitsof Whole-Body Electromyostimulation Users: A Pilot Study

The importance of physical activity (PA) in people’s health is well known. Today, sedentary lifestyles constitute a serious risk to global health. The likelihood that an individual will engage in PA depends largely on the perceived benefits and barriers to being physically active. The industry continues to create mechanisms to improve PA practice by minimizing the barriers. Thus, whole-body electrostimulation training (WB-EMS) emerged. Objective: To identify the main barriers and perceived benefits for WB-EMS users and to determine if there are differences between genders. Design: Cross-sectional study with 270 WB-EMS users from five countries. Results: There were no significant differences in barriers and perceived benefits between genders. Perceived benefits: enjoyment (70.3%), increased physical fitness (55.1%), personal accomplishment (53%), improve overall body (51.9%) and increase muscle strength (51.9%); Barriers: Take too much time from family (73.7%), take too much time from responsibilities (71.5%) and physical exercise (PE) takes a lot of time (67.4%). Conclusions: There were no significant differences between genders. The most prominent perceived benefits of using WB-EMS are enjoyment and increased physical health, and the main barriers are related to lack of time.

Gay Dating on Non-dating Platforms: The Case of Online Dating Activities of Gay Men on a Q&A Platform

Gay dating applications, such as Grindr and SCRUFF, are considered the primary platforms for gay men to conduct online dating activities. However, on Zhihu, a Chinese question-and-answer website, tens of thousands of homosexual users have been searching for romantic partners, which suggests that Zhihu may have unique affordances in online dating activities for Chinese gay men. To better understand how Chinese gay men perceive the affordances of a non-dating platform for online dating, we conduct a mixed-methods study, including observations, interviews, and quantitative and qualitative analysis of users' self-presentations. We find that gay men users publish personal ads by answering "fishing questions" on Zhihu. Through our analysis, we examine how users perceive the affordances of Zhihu to satisfy their social and psychological gratifications at the self, community, and audience levels. Although gay users face the risk of disclosing homosexual identity on mainstream social media, they perceive such risk as acceptable for better online dating experience. We discuss how users respond to severe social stigma in China, and the gap between user needs and the design of gay dating applications. We elaborate on the implications of our findings to discuss the potential benefits for LGBTQ users if LGBTQ service providers collaborate with social media.

Sustainable electricity supply for small off-grid communities in Colombia: A system dynamics approach

Colombia, like many other low and middle-income countries, faces an electricity access deficit. Even where access is available, many off-grid communities are only provided with a few hours of service, typically using diesel, which is expensive and polluting. Using a system dynamics model, this paper investigates how a sustainable and durable electricity supply can be provided in off-grid communities in Colombia. The scenarios examined draw on two government funds that have been established to: deliver the infrastructure and provide subsidies for electricity supply. The results demonstrate that a transition from diesel to renewables is not only possible but also economically viable and desirable. The simulations also show that in order to make the best use of limited government funding for electrification, the transition from diesel to renewables should begin as soon as possible and be accompanied by a zero-diesel policy by 2040. Furthermore, the model highlights that electricity systems should be designed to enable gradual growth in demand – driven by socio-economic development and productive uses. Given the imperative to provide a sustainable and durable electricity supply to off-grid communities, this paper provides insights into how this can be achieved while delivering clear benefits for users, utilities and the government.

GO-Finder: A Registration-free Wearable System for Assisting Users in Finding Lost Hand-held Objects

People spend an enormous amount of time and effort looking for lost objects. To help remind people of the location of lost objects, various computational systems that provide information on their locations have been developed. However, prior systems for assisting people in finding objects require users to register the target objects in advance. This requirement imposes a cumbersome burden on the users, and the system cannot help remind them of unexpectedly lost objects. We propose GO-Finder (“Generic Object Finder”), a registration-free wearable camera-based system for assisting people in finding an arbitrary number of objects based on two key features: automatic discovery of hand-held objects and image-based candidate selection. Given a video taken from a wearable camera, GO-Finder automatically detects and groups hand-held objects to form a visual timeline of the objects. Users can retrieve the last appearance of the object by browsing the timeline through a smartphone app. We conducted user studies to investigate how users benefit from using GO-Finder. In the first study, we asked participants to perform an object retrieval task and confirmed improved accuracy and reduced mental load in the object search task by providing clear visual cues on object locations. In the second study, the system’s usability on a longer and more realistic scenario was verified, accompanied by an additional feature of context-based candidate filtering. Participant feedback suggested the usefulness of GO-Finder also in realistic scenarios where more than one hundred objects appear.

Control strategies for large industrial users to participate in interruptible load response considering production characteristics

The interruptible cost benefit of large industrial users is an important factor to decide whether to participate in interruptible load management, which has a direct impact on users’ interruption and the choice of interruption strategy. Different industrial users have different production processes and electricity consumption characteristics. This paper first analyzes the production and power consumption characteristics of users, then analyzes the cost and benefit of large industrial users participating in interruptible load response, as the basis for judging whether users are willing to participate in interruptible load response. Finally, the case study can provide some guidance for enterprises to formulate the response strategy of interruptible load.

Decision Making for Connected Automated Vehicles at Urban Intersections Considering Social and Individual Benefits

To address the coordination issue of connected automated vehicles (CAVs) at urban scenarios, a game-theoretic decision-making framework is proposed that can advance social benefits, including the traffic system efficiency and safety, as well as the benefits of individual users. Under the proposed decision-making framework, in this work, a representative urban driving scenario, i.e. the unsignalized intersection, is investigated. Once the vehicle enters the focused zone, it will interact with other CAVs and make collaborative decisions. To evaluate the safety risk of surrounding vehicles and reduce the complexity of the decision-making algorithm, the driving risk assessment algorithm is designed with a Gaussian potential field approach. The decision-making cost function is constructed by considering the driving safety and passing efficiency of CAVs. Additionally, decision-making constraints are designed and include safety, comfort, efficiency, control and stability. Based on the cost function and constraints, the fuzzy coalitional game approach is applied to the decision-making issue of CAVs at unsignalized intersections. Two types of fuzzy coalitions are constructed that reflect both individual and social benefits. The benefit allocation in the two types of fuzzy coalitions is associated with the driving aggressiveness of CAVs. Finally, the effectiveness and feasibility of the proposed decision-making framework are verified with three test cases.

Digital Forensic Analysis of Discord Mobile Application on Android Based Smartphones

Nowadays, the spread of social media in all areas of society and becoming a part of life has led to creative and innovative changes in the fields of communication. Instant messaging applications are widely used in communication between users around the world, and the Discord application is one of them. With the Discord application, more than 300 million registered users benefit from many services such as gaming, messaging, and video chat. The use of Discord by cybercriminals has also become one of the most common applications in forensic investigations. In this study, by examining the structure of the Discord application used in Android devices, a methodology has been presented on how to extract data and how to examine these data in terms of forensic analysis. The proposed analysis methodology shows how communication analytics, contact information, message information, deleted messages, group messages, how messages are extracted and how to examine these data structures, permissions, user information, and communication protocols can be analyzed. In the results of the study, a comprehensive analysis of the Discord application in terms of judicial reviews is presented.

Augmented Analytics Driven by AI: A Digital Transformation beyond Business Intelligence.

Lately, Augmented Analytics (AA) has increasingly been introduced as a tool for transforming data into valuable insights for decision-making, and it has gained attention as one of the most advanced methods to facilitate modern analytics for different types of users. AA can be defined as a combination of Business Intelligence (BI) and the advanced features of Artificial Intelligence (AI). With the massive growth in data diversity, the traditional approach to BI has become less useful and requires additional work to obtain timely results. However, the power of AA that uses AI can be leveraged in BI platforms with the use of Machine Learning (ML) and natural language comprehension to automate the cycle of business analytics. Despite the various benefits for businesses and end users in converting from BI to AA, research on this trend has been limited. This study presents a comparison of the capabilities of the traditional BI and its augmented version in the business analytics cycle. Our findings show that AA enhances analysis, reduces time, and supports data preparation, visualization, modelling, and generation of insights. However, AI-driven analytics cannot fully replace human decision-making, as most business problems cannot be solved purely by machines. Human interaction and perspectives are essential, and decision-makers still play an important role in sharing and operationalizing findings.

Ten questions concerning human-building interaction research for improving the quality of life

This paper seeks to address ten questions that explore the burgeoning field of Human-Building Interaction (HBI), an interdisciplinary field that represents the next frontier in convergent research and innovation to enable the dynamic interplay of human and building interactional intelligence. The field of HBI builds on several existing efforts in historically separate research fields/communities and aims to understand how buildings affect human outcomes and experiences, as well as how humans interact with, adapt to, and affect the built environment and its systems, to support buildings that can learn, enable adaptation, and evolve at different scales to improve the quality-of-life of its users while optimizing resource usage and service availability. Questions were developed by a diverse group of researchers with backgrounds in design, engineering, computer science, social science, and health science. Answers to these questions draw conclusions from what has been achieved to date as reported in the available literature and establish a foundation for future HBI research. This paper aims to encourage interdisciplinary collaborations in HBI research to change the way people interact with and perceive technology within the context of buildings and inform the design, construction, and operation of next-generation, intelligent built environments. In doing so, HBI research can realize a myriad of benefits for human users, including improved productivity, health, cognition, convenience, and comfort, all of which are essential to societal well-being.

P-082 INNOVATION IN INGUINAL HERNIA REPAIR

Abstract Aim Innovation is to efficiently use knowledge to improve an existing process for the benefit of users and their environment. The aim is to show different innovations that we are applying in inguinal hernia repair. Material & Methods We present: 1. data from the first 500 procedures using 5mm articulated instruments. 2. Postoperative sports rehabilitation protocol designed to improve quality of life. 3. Virtual interactive visits (VIV) to teach and learn at a distance allows interaction in the operating room between a specialist and the surgeon in training. Results The articulated forceps allow angulations in order to reach areas with less pulling force and movements. The accepted benefits of robotics have been achieved without significant cost impact. The sport rehabilitation protocol after laparoscopic hernioplasty does not increase recurrence rate or complications. It probably accelerates the return to regular physical activity, improving the quality of life in the postoperative period. The (VIV) allows us to carry out the training process of specialists from Buenos Aires to Latin America and Spain, ​​modifying and improving the education and training of the new generations. Conclusions The articulated graspers, the sports rehabilitation protocol, and the virtual interactive visits allow us to innovate in tools, quality of life, and education.

Agile Research Data Management with FDOs using LinkAhead

Agile Research Data Management with FDOs using LinkAhead

Crowding in Public Transport: A Review of Objective and Subjective Measures

Crowding in public transport is becoming a growing concern as demand grows at a rate that is outstripping available capacity. To capture the user benefits associated with reduced crowding from improved public transport, it is necessary to identify the relevant dimensions of crowding that are meaningful measures of what crowding means to travelers. There are a number of objective and subjective measures of crowding promoted in the literature, with some objective measures being used as the basis of a standard of acceptable levels of practice. There is a disconnection between objective measures and subjective measures, the latter representing what matters to users. We illustrate the difference in a comparison of monitored crowding levels using crowding measures defined by the rail operator/authority in Sydney and Melbourne, Australia, and the level of crowding experienced by rail passengers from two recent surveys to reveal the significant gap between objective and subjective measures of crowding.

University Traveler Value of Potential Real-Time Transit Information

Intelligent transportation systems (ITS) have become common in public transit systems, particularly providing real-time transit information. For new implementations, it remains difficult to predict and quantify system and user benefits of technology implementation. Although previous studies have quantified the operational benefits of real-time transit traveler information systems, a gap in knowledge exists around passenger benefits of such systems. The objective of this research was to create a refined method for evaluating transit rider benefits from real-time traveler information and predict changes in traveler behavior. The study was conducted on a rural university campus, isolating the impacts of the system from the multiple influences that often affect transportation in larger metropolitan areas. This study uniquely integrated transit system performance, pedestrian travel times, and traffic simulation to determine travel times and predict mode split. Findings indicated that reducing passenger waiting anxiety was the most significant measure of traveler benefit from such a system. While the benefits found were specific to the study site, the methodology can be used for other transit systems evaluating real-time transit technology investments in rural or urban environments.

An effective service trust evaluation and preprocessing approach considering multi-user interests in cloud manufacturing

In the cloud manufacturing (CMfg) platform, there are numerous manufacturing services with same or similar functions. Due to the inconsistency of service quality, how to effectively evaluate the quality of services is a fundamental problem in CMfg, and which aims to reduce risk and increase the benefits of users. Under these contexts, this study first constructs a comprehensive three-dimensional trust evaluation system that considers the trust of service demanders, resource providers, and cloud platform operators in CMfg. And then, a manufacturing services trust evaluation and preprocessing model is proposed, and the optimization process is described as following: (1) superior and inferior manufacturing services are identified by the first stage filtration; and (2) inferior manufacturing services are further classified by the second stage filtration. After that, to deal with the concerned problem, an improved multi-objective non-dominated sorting genetic algorithm III (IMO-NSGA-III) is developed to find the Pareto-optimal solutions. Furthermore, nine random instances are designed to show that the proposed IMO-NSGA-III outperforms other three state-of-the-art algorithms in terms of convergence and diversity. Finally, three case studies that comes from an automotive parts assembly company is employed, and the effectiveness of the proposed model and IMO-NSGA-III algorithm is further demonstrated.

Network Rebalance and Operational Efficiency of Sharing Transportation System: Multi-Objective Optimization and Model Predictive Control Approaches

Sharing transportation systems can significantly promote travelers convenience and efficiency. As a vital part, bike-sharing system (BSS) has effectively solved “the-last-mile” problem during transportation interchange, but bike imbalance between docks severely deteriorates operational efficiency of BSS. In this paper, we present multi-objective optimization and predictive control approaches to tackle the bike rebalancing problem, where optimal redistributing strategies can maximize the operational efficiency of BSS with respects to equilibrium state and redistribution cost. A dock-based BSS dynamic network is modeled based on a proximity graph, in which connection relation, bike usage, and redistribution flow are formulated. To measure the operational efficiency, a performance metric is presented to consider both benefits of user and operator. To satisfy bike renting, returning, and redistributing requirements, model predictive control (MPC) is then employed to compute feasible and optimal redistribution strategies based on the network model. The effectiveness of multi-objective optimization and MPC is verified on different topologies of BSS. Experimental results show that when the BSS reaches the equilibrium state, the operational efficiency will be maximized in the proposed approaches.

Harnessing power of simulation training effectiveness with Kirkpatrick model in emergency surgical airway procedures

ObjectivesTraining effectiveness indicates how good a program has met pre-set training objectives or organizational goals for the best benefit of healthcare professionals and service users in the community. The study aimed to evaluate training effectiveness following implementation of new training curriculum of emergency surgical airway procedures (Cricothyroidotomy) organized by the Queen Elizabeth Hospital. DesignThis training evaluation relied on observational descriptive study design. Timed task on Cricothyroidotomy procedures and standardized post-training questionnaire were applied to assess the first 3 levels of Kirkpatrick's model: (Level-1) Reaction by training satisfaction; (Level-2) Learning by acquisition of knowledge and skills assessment passing rate; (Level-3) Behavior by personal strengths. SettingThis program was operated in the Multi-Disciplinary Simulation and Skills Centre, a hospital-based high-fidelity simulation training center accredited by the Society for Simulation in Healthcare. ParticipantsThe study recruited 80 trauma service providers, including 35 general surgeons, 15 emergency physicians, 10 anesthesiologists or intensivists, 6 neurosurgeons, 4 orthopedic surgeons, and 10 emergency nurses from five trauma centers under the Hospital Authority. All underwent the Advanced Trauma Life Support training in advance. ResultsCompared with reference score from previous training sessions, the result of program using new training curriculum and simulator demonstrated significant training satisfaction of participants (Level-1), and high level of assertiveness, mental preparedness, self-efficacy, and internal locus of control and responsibility (p < .01, for all in Level-3). All participants (N = 80) completed entire Cricothyroidotomy procedure in 2 min without technical errors (Assessment passing rate = 100%) (Level-2). ConclusionsUnder Kirkpatrick model, simulation training in Cricothyroidotomy procedure using new curriculum and simulators has been proven to be useful for healthcare professionals involved in trauma service management. The result suggests that application of a state-of-the-art training tools to advanced surgical skills training could improve training satisfaction, knowledge and skills acquisition, and personal strengths transferable to clinical practice. ACGME competenciesPractice Based Learning and Improvement.

Attractive infrastructure for everyone? Different preferences for route characteristics among cyclists

• Large-scale stated-preference experiment to evaluate bike route choice behavior. • Higher route requirements for all analyzed subgroups compared to overall population. • Evidence of positive effect of lower car speeds for older cyclists and those with kids. • Vulnerable road users benefit stronger from bike-friendly infrastructure. Knowing about the specific route preferences of demographic groups is crucial when researching equity in cycling. In this study, we use a large-scale stated-preference experiment with 4389 respondents and 35,112 choice observations to evaluate route choice behavior. We set up discrete route choice models and focus on the specific needs of women, people cycling with children, and older adults. Results show that all groups of interest show higher, but not fundamentally different, route requirements. In this context, lower speed limits for motorized transport are very important for people cycling with children, and older adults. In addition, women and those traveling with children attach significantly higher value to separated bike infrastructure. These results show that vulnerable road users benefit stronger from a bike-friendly road infrastructure than the cyclist population as a whole.

Impact of monetary and non-monetary social functions on users' knowledge-sharing intentions in online social Q&A communities

PurposeWith the rapid development of paid online social question and answer (Q&A) communities, monetary social functions have been introduced and have potential benefits for both platforms and users. However, these functions' impact on knowledge contribution remains uncertain. This study proposes a conceptual model based on the stimulus–organism–response framework, according to which monetary and non-monetary social functions can help nurture short-term and long-term relationships among community users, and thereafter improves social identity and knowledge-sharing intentions.Design/methodology/approachThis study selects Zhihu, a famous online social Q&A community in China, and conducts an online survey to collect data from its frequent users. A sample of 286 valid questionnaires was collected to test our research model by using a structural equation modeling method. In addition, a bootstrapping approach is used to test the mediation effect.FindingsResults indicate that monetary social functions help nurture short-term and long-term relationships among community users. However, non-monetary social functions only affect short-term relationships directly. Short-term and long-term relationships both have a positive relationship with social identity and thereafter improve users' knowledge-sharing intentions.Originality/valueThis study focuses on users' knowledge-sharing intentions in Q&A communities from the perspective of social. Specifically, we separated social functions in Q&A platforms into monetary and non-monetary ones and explored their impact on the development of short-term and long-term relationships. Results demonstrate the importance of monetary social functions and explain how monetary and non-monetary social functions affect users' knowledge-sharing intentions in different approaches.