Deep Room Recognition Using Inaudible Echos

Recent years have seen the increasing need of location awareness by mobile applications. This paper presents a room-level indoor localization approach based on the measured room's echos in response to a two-millisecond single-tone inaudible chirp emitted by a smartphone's loudspeaker. Different from other acoustics-based room recognition systems that record full-spectrum audio for up to ten seconds, our approach records audio in a narrow inaudible band for 0.1 seconds only to preserve the user's privacy. However, the short-time and narrowband audio signal carries limited information about the room's characteristics, presenting challenges to accurate room recognition. This paper applies deep learning to effectively capture the subtle fingerprints in the rooms' acoustic responses. Our extensive experiments show that a two-layer convolutional neural network fed with the spectrogram of the inaudible echos achieve the best performance, compared with alternative designs using other raw data formats and deep models. Based on this result, we design a RoomRecognize cloud service and its mobile client library that enable the mobile application developers to readily implement the room recognition functionality without resorting to any existing infrastructures and add-on hardware. Extensive evaluation shows that RoomRecognize achieves 99.7%, 97.7%, 99%, and 89% accuracy in differentiating 22 and 50 residential/office rooms, 19 spots in a quiet museum, and 15 spots in a crowded museum, respectively. Compared with the state-of-the-art approaches based on support vector machine, RoomRecognize significantly improves the Pareto frontier of recognition accuracy versus robustness against interfering sounds (e.g., ambient music).Comment: 29 page

Environment, Marketing Strategy, Performance, and International Exit: Why and How They Are Connected ——A Study on International Exit in the Chinese Outward Foreign Direct Investment (OFDI) Context

Although research on foreign market entry and expansion behaviour has attracted significant interest in the literature, there is a general lack of research (both conceptual and empirical) on the exit behaviour of Foreign Direct Investment (FDI) firms. To address this issue, the current study develops a conceptual framework by extending the Environment-Strategy-Performance (ESP) paradigm to include the exit decision as a consequence of current performance. This thesis draws notions from various theories including the ESP paradigm, fit theory, dynamic capabilities (DC) theory, and the theory of competitive advantage. The objective is to take an initial step towards reducing the discrepancy between previous conceptual research and empirical research on exit, by developing a conceptual framework and empirically examining it in the context of Chinese Outward Foreign Direct Investment (OFDI). It also aims to lay the conceptual foundation for subsequent empirical research on international marketing and international exit. Several research hypotheses are advanced and tested using questionnaire survey data. The main research results show that both dissatisfactory performance of a foreign affiliate, and the internal strategic misfit between a foreign affiliate and its headquarters are important triggers of the exit decision. However, when the moderating role of a foreign affiliate’s marketing capabilities is considered, the impact of strategic misfit on the exit decision becomes not significant, whereas the influence of dissatisfactory performance on the exit decision remains significant. The research results have generated new insights into both international marketing strategy and international exit behaviour. Implications for both headquarters’ managers and foreign affiliates’ managers are also discussed

Online-offline activities and game-playing behaviors of avatars in a massive multiplayer online role-playing game

Massive multiplayer online role-playing games (MMORPGs) are very popular in China, which provides a potential platform for scientific research. We study the online-offline activities of avatars in an MMORPG to understand their game-playing behavior. The statistical analysis unveils that the active avatars can be classified into three types. The avatars of the first type are owned by game cheaters who go online and offline in preset time intervals with the online duration distributions dominated by pulses. The second type of avatars is characterized by a Weibull distribution in the online durations, which is confirmed by statistical tests. The distributions of online durations of the remaining individual avatars differ from the above two types and cannot be described by a simple form. These findings have potential applications in the game industry.Comment: 6 EPL pages including 10 eps figure

Privacy protection for RFID-based tracking systems

Abstract—RFID technology is increasingly being deployed in ubiquitous computing environments for object tracking and localization. Existing tracking architecture usually assumes the use of a trusted server which is invulnerable to compromise by internal and external adversaries. However, maintaining such a trusted server is unlikely in the real world. In this paper, we consider the problem of adding privacy protection to object tracking systems built upon passive RFID tags, without relying on a trusted server assumption. Our protocol continues to protect user privacy in the event of partial compromise of a server. I

Division of labor, skill complementarity, and heterophily in socioeconomic networks

Constituents of complex systems interact with each other and self-organize to form complex networks. Empirical results show that the link formation process of many real networks follows either the global principle of popularity or the local principle of similarity or a tradeoff between the two. In particular, it has been shown that in social networks individuals exhibit significant homophily when choosing their collaborators. We demonstrate, however, that in populations in which there is a division of labor, skill complementarity is an important factor in the formation of socioeconomic networks and an individual's choice of collaborators is strongly affected by heterophily. We analyze 124 evolving virtual worlds of a popular "massively multiplayer online role-playing game" (MMORPG) in which people belong to three different professions and are allowed to work and interact with each other in a somewhat realistic manner. We find evidence of heterophily in the formation of collaboration networks, where people prefer to forge social ties with people who have professions different from their own. We then construct an economic model to quantify the heterophily by assuming that individuals in socioeconomic systems choose collaborators that are of maximum utility. The results of model calibration confirm the presence of heterophily. Both empirical analysis and model calibration show that the heterophilous feature is persistent along the evolution of virtual worlds. We also find that the degree of complementarity in virtual societies is positively correlated with their economic output. Our work sheds new light on the scientific research utility of virtual worlds for studying human behaviors in complex socioeconomic systems.Comment: 14 Latex pages + 3 figure