Statistics for Spatial Data.

The theory of affordances

Urbanization's rapid progress has modernized many people's lives but also engendered big issues, such as traffic congestion, energy consumption, and pollution. Urban computing aims to tackle these issues by using the data that has been generated in cities (e.g., traffic flow, human mobility, and geographical data). Urban computing connects urban sensing, data management, data analytics, and service providing into a recurrent process for an unobtrusive and continuous improvement of people's lives, city operation systems, and the environment. Urban computing is an interdisciplinary field where computer sciences meet conventional city-related fields, like transportation, civil engineering, environment, economy, ecology, and sociology in the context of urban spaces. This article first introduces the concept of urban computing, discussing its general framework and key challenges from the perspective of computer sciences. Second, we classify the applications of urban computing into seven categories, consisting of urban planning, transportation, the environment, energy, social, economy, and public safety and security, presenting representative scenarios in each category. Third, we summarize the typical technologies that are needed in urban computing into four folds, which are about urban sensing, urban data management, knowledge fusion across heterogeneous data, and urban data visualization. Finally, we give an outlook on the future of urban computing, suggesting a few research topics that are somehow missing in the community.

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Urban Computing: Concepts, Methodologies, and Applications

Design of a distributed energy-efficient clustering algorithm for heterogeneous wireless sensor networks

A wireless sensor network (WSN) consisting of a large number of tiny sensors can be an effective tool for gathering data in diverse kinds of environments. The data collected by each sensor is communicated to the base station, which forwards the data to the end user. Clustering is introduced to WSNs because it has proven to be an effective approach to provide better data aggregation and scalability for large WSNs. Clustering also conserves the limited energy resources of the sensors. This paper synthesises existing clustering algorithms in WSNs and highlights the challenges in clustering.

A survey on clustering algorithms for wireless sensor networks

A self-organizing peer-to-peer system is built upon an application level overlay, whose topology is independent of an underlying physical network. A well-routed message path in such systems may result in a long delay and excessive traffic due to the mismatch between logical and physical networks. In order to solve this problem, we present a family of Peer-exchange Routing Optimization Protocols (PROP) to reconstruct the overlay. It includes two policies: PROP-G for generic condition and PROP-O for optimized one. Both theoretical analysis and simulation experiments show that these two protocols greatly reduce the average latency of the overlay and achieve a better logical topology with low overhead. Their overall performance can be further improved if combined with other recent approaches. Specifically, PROP-G can be easily applied to both structured and unstructured systems without the loss of their primary characteristics, such as efficient routing and anonymity. PROP-O, on the other hand, is more efficient, especially in a heterogenous environment where nodes have different processing capabilities.

Peer-exchange schemes to handle mismatch in peer-to-peer systems

In this paper, we aim to develop a travelogue service to discover and convey various travelogue digests, in form of theme locations and geographical scope to their readers. In this service, theme locations in a travelogue are the core information to discover. Due to the inherent ambiguity of location relevance, we explore the textual (e.g., surrounding words) and geographical (e.g., geographical relationship among locations) features of locations to perform location relevance classification for theme location discovery. Finally, we conduct comprehensive experiments on collected travelogues to evaluate the performance of our location relevance classification technique and demonstrate the effectiveness of the travelogue service.

/pdf/location-relevance-classification-for-travelogue-digests-2r4e6i2k8v.pdf

Location relevance classification for travelogue digests

We present an analysis of user conversations in on-line social media and their evolution over time. We propose a dynamic model that accurately predicts the growth dynamics and structural properties of conversation threads. The model successfully reconciles the differing observations that have been reported in existing studies. By separating artificial factors from user behaviors, we show that there are actually underlying rules in common for on-line conversations in different social media websites. Results of our model are supported by empirical measurements throughout a number of different social media websites.

From User Comments to On-Line Conversations

After experiencing the COVID-19 pandemic, employees' health and well-being become a priority for firms. Organizational health-oriented strategies assist them in coping with health-related crises. Based on the social exchange theory, the present study attempts to determine the role of organizational health-oriented strategies in promoting employees' job performance. This study hypothesized that the organizations' health-oriented strategies positively correlate with employees' job performance. This study also assessed the mediating role of employees' psychological wellbeing and trust and moderating role of perceived medical mistrust. For the empirical examination, data of the present study was gathered from the textile sector in China. This study analyzed data through partial least square structural equation modeling (PLS-SEM). For this purpose, Smart-PLS software was used. The outcomes revealed that organizational health-oriented strategies positively enhance the employees' psychological wellbeing, trust, and job performance. Moreover, the results revealed that employees' psychological wellbeing and trust positively mediate the proposed relationships. This study found that perceived medical mistrust moderates the relationship between employees' psychological wellbeing and job performance. However, the findings revealed that perceived medical mistrust does not moderate the relationship between employees' trust and job performance. In addition, the present study's findings provide insights to the firms about the importance of health-oriented strategies. Moreover, this study's findings also serve the literature by providing important theoretical and practical implications.

Impact of organizational health-oriented strategies on employees' job performance, perceived medical mistrust as a moderator: A COVID-19 perception-based view

Mao Ye

Papers

Peer-exchange schemes to handle mismatch in peer-to-peer systems

Location relevance classification for travelogue digests

From User Comments to On-Line Conversations

Impact of organizational health-oriented strategies on employees' job performance, perceived medical mistrust as a moderator: A COVID-19 perception-based view