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Pedestrian Path Generation through GPS Traces
Published in Hassan A. Karimi, Advanced Location-Based Technologies and Services, 2016
Piyawan Kasemsuppakorn, Hassan A. Karimi
Clearly, none of the aforementioned techniques is suitable for automatically constructing pedestrian networks. This chapter explores techniques for extracting pedestrian networks from road networks and collected GPS traces. Interest in location-based social networking (LBSN) (Karimi et al. 2009; Fusco, Michael, and Michael 2010) and the rapid adoption of mobile devices by a wide variety of users are facilitating the collection of GPS traces. Through LBSN people can broadcast their current location, search for nearby friends, and share their opinions or activities with friends using blogs, photos, or music with spatial coordinates and time (Fusco, Michael, and Michael 2010). Members of LBSNs can be both contributors, providing digital content, and consumers, using the content provided by other members. Any user-generated content related to spatial data is called volunteered geographic information (VGI) (see Goodchild 2007). With the availability of GPS-enabled mobile phones, people can now collect GPS traces of where they are and where they have been in an unobtrusive and continuous manner. VGI has facilitated collaborative geospatial content and crowdsourcing as a means of collecting real-world GPS traces that can be used for map generation. Potential contributors of real-world GPS traces include volunteers and general mobile social network members. Volunteers can collect GPS traces for the creation of a base map, for example, see the OSM project (Haklay and Weber2008), while members of LBSNs could provide data such as health and leisure, where GPS traces are a by-product of users’ activities.
Survey of Sybil Attacks in Networks
Published in Mohammad Ilyas, Sami S. Alwakeel, Mohammed M. Alwakeel, el-Hadi M. Aggoune, Sensor Networks for Sustainable Development, 2017
In mobile social networks, our system consists of two parts: a remote server and several users, as shown in Figure 21.12. The server is responsible for two jobs: (1) storing and periodically pruning the created signed network graph and (2) assigning randomly sampled social profiles to users for computing the trust level between users. Note that now we are using two networks: a mobile social network and a created signed social network. The mobile social network is the network formed by physical interactions of phone users, while the signed network is created for Sybil detection. The positive edges on the created signed social network represent trusted social relationships, which could be obtained from an online-social network. The negative edges are generated based on users’ physical interactions with each other. We assume that each honest user has one mobile phone, which is associated with a single real identity, while the attacker may hold more than one phone, and each phone runs multiple fake identities. Each identity is required to periodically send a special message to the server, and the server will return updated social profiles; otherwise, the identity will be deleted from the system. Unlike traditional social network–based Sybil defense models, we assume that the honest region of a social network may not be fast mixing. Exactly how many honest communities may be formed is determined by the social networks being considered. For instance, if we use a social network of political opinions, then the honest nodes may be gathered into two communities, for example, the Democratic and Republican parties. However, if we adopt Facebook, the honest users may only be clustered into one community.
Wearable Localization via Mobile Crowd Sensing
Published in Kaikai Liu, Xiaolin Li, Mobile SmartLife via Sensing, Localization, and Cloud Ecosystems, 2017
Family Group As shown in Fig. 9.1, we define the family group as a virtually connected unit via peer-to-peer communication channels. The smartphone and the wearable tag are necessary components for connecting this group. The family’s leader could initialize this group by adding all of its nearby devices via pairing. The family leader needs to use the smartphone with BLE functionality, and install our mobile social network app. The family member could use either a smartphone (with BLE functionality and “FindingNemo” app) or a wearable tag. Users could give big kids a smartphone, and give wearable tags to little kids and pets.
An Exploration of Motivations for Online Identity Reconstruction from the Perspective of Social Learning Theory
Published in International Journal of Human–Computer Interaction, 2023
The integration of online and offline channels has a significant impact on people’s behavior. For example, it is found that individuals who perceive higher online-offline integration are more likely to become addicted to mobile social network services (Yang et al., 2016). A previous study also found that the online-offline integration of people’s social lives will increase the amount of time spent and frequency of communication on social network platforms, which in turn may lead to a higher level of mobile technology dependence (Douglas et al., 2008). Additionally, the existing study suggested that online-offline integration enables people to use social media for collecting information about potential friends and use that information to decide whether they are suitable for further offline connections (Standlee, 2019).
A gender perspective on the use of mobile social network applications to enhance the social well-being of people with physical disabilities: the mediating role of sense of belonging
Published in Behaviour & Information Technology, 2023
The rapid development of mobile social network applications (MSNA) has demonstrated their potential to be used by people with physical disabilities (PPD) to improve their quality of life and mitigate their social inclusion (Lin, Yang, and Zhang 2018). Such applications also assist PPD in China to improve their quality of life—it has been proven that MSNA help PPD become involved in society and offer them a greater sense of belonging in relation to community involvement. MSNA help PPD to provide and receive social support through online social interaction (Foley and Ferri 2012; McClimens and Gordon 2009). Contradictorily, it is claimed that MSNA results in future and deeper digital exclusion of PPD (Ellcessor 2016; Lin, Yang, and Zhang 2018). This is because studies focused on people with disability found that although PPD have access to society, they face greater risks online as well as negative effects of online communication (Chadwick and Wesson 2016; Chadwick, Wesson, and Fullwood 2013). However, the effects of MSNA on those PPD who only have mobility-related disabilities have been difficult to identify. In addition, previous studies have not investigated the relationship between MSNA and PPD. Thus, determining whether MSNA could improve PPD’s social life and well-being is crucial.
Sustainability in supply chains: reappraising business process management
Published in Production Planning & Control, 2023
Kate Mc Loughlin, K. Lewis, D. Lascelles, S. Nudurupati
Aligned with extant literature (Ardito et al. 2019c; Luthra and Mangla 2018), there were numerous examples of technology in mapping the supply chain network, which results in greater traceability and transparency—both critical practices for successful sustainable supply chain integration. Our study shows this is creating a trend across leading sustainability organisations for publishing their supply chain network maps online. Another technology-driven SSCM outcome is how the network information is used in conjunction with online and mobile social network technologies to share information and improve decision making (Tseng et al. 2019). This includes activities such as open-source, events, platforms, digital media, workshops/training, and building globally dispersed communities. For example, M&S and Tesco have created online supplier networks and management systems to enhance collaboration and integration, while Solidaridad uses Facebook to share train and develop isolated and illiterate farmers.