324,500 research outputs found
Spirobranchus bakau Shantti & Kupriyanova & Quek & Yap & Teo 2021, sp. nov.
No full textSpirobranchus bakau sp. nov. Figs 2–5; Table 2Published as part of Shantti, Pavarne, Kupriyanova, Elena K., Quek, Zheng Bin Randolph, Yap, Nicholas Wei Liang & Teo, Serena Lay Ming, 2021, Spirobranchus bakau sp. nov. from Singapore: yet another species of S. kraussii-complex (Polychaeta: Serpulidae), pp. 33-65 in Zootaxa 5040 (1) on page 39, DOI: 10.11646/zootaxa.5040.1.2, http://zenodo.org/record/553093
Supplemental Material - Managing Nationalism: Experiments in China
No full textSupplemental Material for Managing Nationalism: Experiments in China by Kai Quek and Samuel S. H. Chan in Journal of Conflict Resolution</p
Supplemental Material - Managing Nationalism: Experiments in China
No full textSupplemental Material for Managing Nationalism: Experiments in China by Kai Quek and Samuel S. H. Chan in Journal of Conflict Resolution</p
Multi-layer Unmanned Aerial Vehicle Networks: Modeling and Performance Analysis
No full textIn this paper, we establish a foundation for the multi-layer aerial networks (MANs), which are modeled as K layer aerial networks (ANs), where each layer has unmanned aerial vehicles (UAVs) with different densities, floating altitudes, and transmission power. To make the framework applicable for various scenarios in MAN, we consider the transmitter- and the receiver-oriented node association rules as well as the air-to-ground and air-to-air channel models, which form line of sight links with a location-dependent probability. We then newly analyze the association probability, the main link distance distribution, successful transmission probability (STP), and area spectral efficiency (ASE) of MAN. The upper bounds of the optimal densities that maximize STP and ASE are also provided. Finally, in the numerical results, we show the optimal UAV densities of each AN that maximize the ASE and the STP decrease with the altitude of the network. We also show that when the total UAV density is fixed for two layer AN, the use of single layer in higher(lower) altitude only for all UAVs can achieve better performance for low(high) total density case. Otherwise, distributing UAVs in two layers, i.e., MAN, achieves better performance.1
Energy effciency of dense wireless sensor networks: To cooperate or not to cooperate
No full textDecentralized detection in a network of wireless
sensor nodes involves the fusion of information about a phenomenon
of interest (PoI) from geographically dispersed nodes.
In this paper, we investigate the problem of binary decentralized
detection in a dense and randomly deployed wireless sensor
network (WSN), whereby the communication channels between
the nodes and the fusion center are bandwidth-constrained. We
consider a scenario in which sensor observations, conditioned on
the alternate hypothesis, are independent but not identically distributed
across the sensor nodes.We compare two different fusion
architectures, namely, the parallel fusion architecture (PFA) and
the cooperative fusion architecture (CFA), for such bandwidthconstrained
WSNs, where each sensor node is restricted to send
a 1-bit information to the fusion center. For each architecture,
we derive expression for the probability of decision error at the
fusion center. We propose a consensus flooding protocol for CFA
and analyze its average energy consumption. We analyze the
effects of PoI intensity, realistic link models, consensus flooding
protocol, and network connectivity on the system reliability and
average energy consumption for both fusion architectures. We
demonstrate that a trade-off exists among spatial diversity gain,
average energy consumption, delivery ratio of the consensus
flooding protocol, network connectivity, node density, and PoI
intensity in CFA. We then provide insight into the design of
cooperative WSNs
Diffusive author(s), cohesive author: Analysis of S/N (1994)
No full textThis study indicates the ways in which various aspects of the author(s) are brought forth in Dumb type’s performance art, the S/N production. Previous research has suggested a non-hierarchical organization of Dumb type and the absence of a “privileged author” in Dumb type’s collaborative work, S/N. However, the results that I have investigated from member’s interviews on the creative process of S/N along with my analysis of the recorded images of S/N, indicate a different aspect of the author(s). First, S/N was created through, so to speak, the collective ideas of the members of Dumb type. Further, S/N has at least nine quotations from previous performances, installations, and printed writings, besides the work-in-progress technique. Explicating one of the “author functions” as given by Michel Foucault, each text has plural subjects of the author. However, it has been revealed from members’ interviews that Teiji Furuhashi had a decision-making role in selecting the members’ ideas within the performance. Since then, S/N has had plural subjects of creation; however, Furuhashi is one of the subjects of creation along with the “privileged author.” S/N has plural authors (diffusive authors) yet at the same time, it has a “privileged author,” Teiji Furuhashi (cohesive author)
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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