8,435 research outputs found
Media Richness and User Continuance to Instant Messaging
Media richness determines adoption of information systems. Insufficient research was done for investigating its influence on user continuance of using instant messaging applications. This study used classic IS and psychological theories to construct a research framework. This study gathered more than 200 responses by using an online form. LISREL software was used to conduct structural equation modeling technique to test the research framework. The findings indicated that various but not all dimensions of media richness positively contribute to users’ continuance to use instant messaging applications. Specific dimensions provide insights for managers to design their applications to effectively retain their users
A wide-band-gap p-type thermoelectric material based on quaternary chalcogenides of Cu2ZnSnQ4 (Q=S,Se)
Chalcopyritelike quaternary chalcogenides, Cu(2)ZnSnQ(4) (Q=S,Se), were investigated as an alternative class of wide-band-gap p-type thermoelectric materials. Their distorted diamondlike structure and quaternary compositions are beneficial to lowering lattice thermal conductivities. Meanwhile, partial substitution of Cu for Zn creates more charge carriers and conducting pathways via the CuQ(4) network, enhancing electrical conductivity. The power factor and the figure of merit (ZT) increase with the temperature, making these materials suitable for high temperature applications. For Cu(2.1)Zn(0.9)SnQ(4), ZT reaches about 0.4 at 700 K, rising to 0.9 at 860 K
A promising p-type transparent conducting material: Layered oxysulfide
Sr3Cu2Sc2O5S2, a layered oxysulfide, composed of anti-PbO-like [Cu2S2] slabs alternating with perovskitelike [Sr3Sc2O5] slabs, was systematically studied as a p-type transparent conducting material. The material has a wide energy gap of 3.1 eV and a p-type electrical conductivity of 2.8 S cm−1 at room temperature. The hole mobility of +150 cm2 V−1 S−1 at room temperature, which is much higher than the typical value of ~10−1–10 cm2 V−1 S−1 found in other copper compounds. The performances of bulk undoped Sr3Cu2Sc2O5S2 show the promise of copper oxysulfides as a class of p-type transparent conductive materials that is essential for optoelectronic applications
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Multi-task learing for subspace segmentation
Subspace segmentation is the process of clustering a set of data points that are assumed to lie on the union of multiple linear or affine subspaces, and is increasingly being recognized as a fundamental tool for data analysis in high dimensional settings. Arguably one of the most successful approaches is based on the observation that the sparsest representation of a given point with respect to a dictionary formed by the others involves nonzero coefficients associated with points originating in the same subspace. Such sparse representations are computed independently for each data point via â„“1-norm minimization and then combined into an affinity matrix for use by a final spectral clustering step. The downside of this procedure is two-fold. First, unlike canonical compressive sensing scenarios with ideally-randomized dictionaries, the data-dependent dictionaries here are unavoidably highly structured, disrupting many of the favorable properties of the â„“1 norm. Secondly, by treating each data point independently, we ignore useful relationships between points that can be leveraged for jointly computing such sparse representations. Consequently, we motivate a multi-task learning-based framework for learning coupled sparse representations leading to a segmentation pipeline that is both robust against correlation structure and tailored to generate an optimal affinity matrix. Theoretical analysis and empirical tests are provided to support these claims.Y. Wang is sponsored by the University of Cambridge Overseas Trust. Y. Wang and Q. Ling are partially supported by sponsorship from Microsoft Research Asia. Q. Ling is also supported in part by NSFC grant 61004137. W. Chen is supported by EPSRC Research Grant EP/K033700/1 and the Natural Science Foundation of China 61401018.This is the final version of the article. It first appeared from JMLR via http://jmlr.org/proceedings/papers/v37/wangc15.htm
Distorted HI Gas in the Widely Separated LIRG Arp 256
We present new interferometric HI and CO (1-0) observations of the luminous
infrared source, Arp 256. Arp 256 consists of two spiral galaxies in an early
stage of merging, with a projected nuclear separation of 29 kpc (54") and an
infrared luminosity of 2.0E11 L_sun. Despite the large separation of the
galaxies' nuclei and mildly disrupted stellar components, the HI disks are
found to be strongly disrupted, and the southern galaxy in Arp 256 shows an
elevated star formation efficiency, which is consistent with a nuclear
starburst. Both of these results run contrary to expectations, posing
interesting questions on the physical mechanisms involved in stimulating star
formation during an interaction.Comment: 19 pages, 7 figures. Accepted for publication in AJ. Author added.
Full resolution figures available at
http://astro.uchicago.edu/home/web/jchen/arp25
Update propagation algorithms for supporting disconnected write in mobile wireless systems with data broadcasting capability
We develop and analyze algorithms for propagating updates by mobile hosts in wireless client-server environments that support disconnected write operations, with the goal of minimizing the tuning time for update propagation to the server. These algorithms allow a mobile host to update cached data objects while disconnected and propagate the updates to the server upon reconnection for conflict resolutions. We investigate two algorithms applicable to mobile systems in which invalidation reports/data can be broadcast to mobile hosts periodically. We show that there exists an optimal broadcasting period under which the tuning time is minimized for update propagations. We perform a comparative analysis between these two update propagation algorithms that rely on broadcasting data and an algorithm that does not, and identify conditions under which an algorithm should be applied to reduce the total tuning time for update propagation by the mobile user to save the valuable battery power and avoid high communication cost. For real-time applications, we address the tradeoff between tuning time and access time with the goal to select the best update propagation algorithm that can minimize the tuning time while satisfying the imposed real-time deadline constraint. The analysis result is applicable to file/data objects that mobile users may need to modify while on the move
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