The Experts below are selected from a list of 172674 Experts worldwide ranked by ideXlab platform
Victor Joo Chuan Tong - One of the best experts on this subject based on the ideXlab platform.
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effects of cultural tightness looseness and social Network Density on expression of positive and negative emotions a large scale study of impression management by facebook users
Personality and Social Psychology Bulletin, 2018Co-Authors: Pan Liu, David Chan, Lin Qiu, William Tov, Victor Joo Chuan TongAbstract:Using data from 13,789 Facebook users across U.S. states, this study examined the main effects of societal-level cultural tightness-looseness and its interaction effects with individuals' social Network Density on impression management (IM) in terms of online emotional expression. Results showed that individuals from culturally tight (vs. loose) states were more likely to express positive emotions and less likely to express negative emotions. Meanwhile, for positive emotional expression, there was a tightness-looseness by social Network Density interaction effect. In culturally tight states, individuals with dense (vs. sparse) Networks were more likely to express positive emotions, while in culturally loose states this pattern was reversed. For negative emotional expression, however, no such interaction was observed. Our findings highlight the influence of cultural norms and social Network structure on emotional expressions as IM strategies.
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Supplementary Material, PSPB-17-106.R2_MethodologyFile – Effects of Cultural Tightness–Looseness and Social Network Density on Expression of Positive and Negative Emotions: A Large-Scale Study of Impression Management by Facebook Users
2018Co-Authors: Pan Liu, David Chan, Lin Qiu, William Tov, Victor Joo Chuan TongAbstract:Supplementary Material, PSPB-17-106.R2_MethodologyFile for Effects of Cultural Tightness–Looseness and Social Network Density on Expression of Positive and Negative Emotions: A Large-Scale Study of Impression Management by Facebook Users by Pan Liu, David Chan, Lin Qiu, William Tov and Victor Joo Chuan Tong in Personality and Social Psychology Bulletin
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Supplementary Material, PSPB-17-106.R2_SupplementaryFile – Effects of Cultural Tightness–Looseness and Social Network Density on Expression of Positive and Negative Emotions: A Large-Scale Study of Impression Management by Facebook Users
2018Co-Authors: Pan Liu, David Chan, Lin Qiu, William Tov, Victor Joo Chuan TongAbstract:Supplementary Material, PSPB-17-106.R2_SupplementaryFile for Effects of Cultural Tightness–Looseness and Social Network Density on Expression of Positive and Negative Emotions: A Large-Scale Study of Impression Management by Facebook Users by Pan Liu, David Chan, Lin Qiu, William Tov and Victor Joo Chuan Tong in Personality and Social Psychology Bulletin
Jeffrey G Andrews - One of the best experts on this subject based on the ideXlab platform.
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Downlink Cellular Network Analysis With Multi-Slope Path Loss Models
IEEE Transactions on Communications, 2015Co-Authors: Xinchen Zhang, Jeffrey G AndrewsAbstract:Existing cellular Network analyses, and even simulations, typically use the standard path loss model where received power decays like $\Vert x\Vert^{-\alpha}$ over a distance $\Vert x\Vert$ . This standard path loss model is quite idealized, and in most scenarios the path loss exponent $\alpha$ is itself a function of $\Vert x\Vert$ , typically an increasing one. Enforcing a single path loss exponent can lead to orders of magnitude differences in average received and interference powers versus the true values. In this paper, we study multi-slope path loss models, where different distance ranges are subject to different path loss exponents. We focus on the dual-slope path loss function, which is a piece-wise power law and continuous and accurately approximates many practical scenarios. We derive the distributions of SIR, SNR, and finally SINR before finding the potential throughput scaling, which provides insight on the observed cell-splitting rate gain. The exact mathematical results show that the SIR monotonically decreases with Network Density, while the converse is true for SNR, and thus the Network coverage probability in terms of SINR is maximized at some finite Density. With ultra-densification (Network Density goes to infinity), there exists a phase transition in the near-field path loss exponent $\alpha_{0}$ : if $\alpha_{0} >1$ unbounded potential throughput can be achieved asymptotically; if $\alpha_{0} , ultra-densification leads in the extreme case to zero throughput.
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downlink cellular Network analysis with multi slope path loss models
arXiv: Information Theory, 2014Co-Authors: Xinchen Zhang, Jeffrey G AndrewsAbstract:Existing cellular Network analyses, and even simulations, typically use the standard path loss model where received power decays like $\|x\|^{-\alpha}$ over a distance $\|x\|$. This standard path loss model is quite idealized, and in most scenarios the path loss exponent $\alpha$ is itself a function of $\|x\|$, typically an increasing one. Enforcing a single path loss exponent can lead to orders of magnitude differences in average received and interference powers versus the true values. In this paper we study \emph{multi-slope} path loss models, where different distance ranges are subject to different path loss exponents. We focus on the dual-slope path loss function, which is a piece-wise power law and continuous and accurately approximates many practical scenarios. We derive the distributions of SIR, SNR, and finally SINR before finding the potential throughput scaling, which provides insight on the observed cell-splitting rate gain. The exact mathematical results show that the SIR monotonically decreases with Network Density, while the converse is true for SNR, and thus the Network coverage probability in terms of SINR is maximized at some finite Density. With ultra-densification (Network Density goes to infinity), there exists a \emph{phase transition} in the near-field path loss exponent $\alpha_0$: if $\alpha_0 >1$ unbounded potential throughput can be achieved asymptotically; if $\alpha_0 <1$, ultra-densification leads in the extreme case to zero throughput.
Xinchen Zhang - One of the best experts on this subject based on the ideXlab platform.
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Downlink Cellular Network Analysis With Multi-Slope Path Loss Models
IEEE Transactions on Communications, 2015Co-Authors: Xinchen Zhang, Jeffrey G AndrewsAbstract:Existing cellular Network analyses, and even simulations, typically use the standard path loss model where received power decays like $\Vert x\Vert^{-\alpha}$ over a distance $\Vert x\Vert$ . This standard path loss model is quite idealized, and in most scenarios the path loss exponent $\alpha$ is itself a function of $\Vert x\Vert$ , typically an increasing one. Enforcing a single path loss exponent can lead to orders of magnitude differences in average received and interference powers versus the true values. In this paper, we study multi-slope path loss models, where different distance ranges are subject to different path loss exponents. We focus on the dual-slope path loss function, which is a piece-wise power law and continuous and accurately approximates many practical scenarios. We derive the distributions of SIR, SNR, and finally SINR before finding the potential throughput scaling, which provides insight on the observed cell-splitting rate gain. The exact mathematical results show that the SIR monotonically decreases with Network Density, while the converse is true for SNR, and thus the Network coverage probability in terms of SINR is maximized at some finite Density. With ultra-densification (Network Density goes to infinity), there exists a phase transition in the near-field path loss exponent $\alpha_{0}$ : if $\alpha_{0} >1$ unbounded potential throughput can be achieved asymptotically; if $\alpha_{0} , ultra-densification leads in the extreme case to zero throughput.
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downlink cellular Network analysis with multi slope path loss models
arXiv: Information Theory, 2014Co-Authors: Xinchen Zhang, Jeffrey G AndrewsAbstract:Existing cellular Network analyses, and even simulations, typically use the standard path loss model where received power decays like $\|x\|^{-\alpha}$ over a distance $\|x\|$. This standard path loss model is quite idealized, and in most scenarios the path loss exponent $\alpha$ is itself a function of $\|x\|$, typically an increasing one. Enforcing a single path loss exponent can lead to orders of magnitude differences in average received and interference powers versus the true values. In this paper we study \emph{multi-slope} path loss models, where different distance ranges are subject to different path loss exponents. We focus on the dual-slope path loss function, which is a piece-wise power law and continuous and accurately approximates many practical scenarios. We derive the distributions of SIR, SNR, and finally SINR before finding the potential throughput scaling, which provides insight on the observed cell-splitting rate gain. The exact mathematical results show that the SIR monotonically decreases with Network Density, while the converse is true for SNR, and thus the Network coverage probability in terms of SINR is maximized at some finite Density. With ultra-densification (Network Density goes to infinity), there exists a \emph{phase transition} in the near-field path loss exponent $\alpha_0$: if $\alpha_0 >1$ unbounded potential throughput can be achieved asymptotically; if $\alpha_0 <1$, ultra-densification leads in the extreme case to zero throughput.
Pan Liu - One of the best experts on this subject based on the ideXlab platform.
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effects of cultural tightness looseness and social Network Density on expression of positive and negative emotions a large scale study of impression management by facebook users
Personality and Social Psychology Bulletin, 2018Co-Authors: Pan Liu, David Chan, Lin Qiu, William Tov, Victor Joo Chuan TongAbstract:Using data from 13,789 Facebook users across U.S. states, this study examined the main effects of societal-level cultural tightness-looseness and its interaction effects with individuals' social Network Density on impression management (IM) in terms of online emotional expression. Results showed that individuals from culturally tight (vs. loose) states were more likely to express positive emotions and less likely to express negative emotions. Meanwhile, for positive emotional expression, there was a tightness-looseness by social Network Density interaction effect. In culturally tight states, individuals with dense (vs. sparse) Networks were more likely to express positive emotions, while in culturally loose states this pattern was reversed. For negative emotional expression, however, no such interaction was observed. Our findings highlight the influence of cultural norms and social Network structure on emotional expressions as IM strategies.
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Supplementary Material, PSPB-17-106.R2_MethodologyFile – Effects of Cultural Tightness–Looseness and Social Network Density on Expression of Positive and Negative Emotions: A Large-Scale Study of Impression Management by Facebook Users
2018Co-Authors: Pan Liu, David Chan, Lin Qiu, William Tov, Victor Joo Chuan TongAbstract:Supplementary Material, PSPB-17-106.R2_MethodologyFile for Effects of Cultural Tightness–Looseness and Social Network Density on Expression of Positive and Negative Emotions: A Large-Scale Study of Impression Management by Facebook Users by Pan Liu, David Chan, Lin Qiu, William Tov and Victor Joo Chuan Tong in Personality and Social Psychology Bulletin
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Supplementary Material, PSPB-17-106.R2_SupplementaryFile – Effects of Cultural Tightness–Looseness and Social Network Density on Expression of Positive and Negative Emotions: A Large-Scale Study of Impression Management by Facebook Users
2018Co-Authors: Pan Liu, David Chan, Lin Qiu, William Tov, Victor Joo Chuan TongAbstract:Supplementary Material, PSPB-17-106.R2_SupplementaryFile for Effects of Cultural Tightness–Looseness and Social Network Density on Expression of Positive and Negative Emotions: A Large-Scale Study of Impression Management by Facebook Users by Pan Liu, David Chan, Lin Qiu, William Tov and Victor Joo Chuan Tong in Personality and Social Psychology Bulletin
Pablo Soldati - One of the best experts on this subject based on the ideXlab platform.
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Spectrum and Network Density Management in 5G Ultra-Dense Networks
IEEE Wireless Communications, 2017Co-Authors: Georgios P. Koudouridis, Pablo SoldatiAbstract:Recent studies argue that optimizing the utilization of the Density of the radio access Network plays a crucial role in fully attaining the spectral efficiency of modern ultra-dense Networks. This insight implicitly unveils a trade-off between the management of spectrum resource and the Network Density that offers new angles to systematically optimize the Network spectral efficiency. Leveraging this tradeoff, this article proposes a framework for joint management of spectrum and Network Density in ultra-dense Networks where the frequency spectrum and the Density of the radio access Network are treated as resources to be jointly optimized to improve the Network spectral efficiency. The generality of this approach is demonstrated in several scenarios, including spectrum and Network Density management for Network slicing, and spectrum sharing among multiple operators of co-located ultra-dense Networks. In the process, we also discuss centralized and distributed architectural solutions for spectrum management where a Network operator is granted either exclusive or non-exclusive access to a portion of the shared spectrum band.
