Deep Learning Based NLOS Identification with Commodity WLAN Devices

Identifying line-of-sight (LOS) and non-LOS (NLOS) channel conditions can improve the performance of many wireless applications, such as signal strength-based localization algorithms. For this purpose, channel state information (CSI) obtained by commodity IEEE 802.11n devices can be used, because it contains information about channel impulse response (CIR). However, because of the limited sampling rate of the devices, a high-resolution CIR is not available, and it is difficult to detect the existence of an LOS path from a single CSI measurement, but it can be inferred from the variation pattern of CSI over time. To this end, we propose a recurrent neural network (RNN) model, which takes a series of CSI to identify the corresponding channel condition. We collect numerous measurement data under an indoor office environment, train the proposed RNN model, and compare the performance with those of existing schemes that use handcrafted features. The proposed method efficiently learns a non-linear relationship between input and output, and thus, yields high accuracy even for data obtained in a very short period.Comment: 9 pages, 9 figures, Accepted for publication in IEEE Transactions on Vehicular Technolog

The role of a diffusion barrier in plasma display panel with the high gamma cathode layer

Plasma display panel (PDP) with MgO-SrO double cathode layer and SiO(2) diffusion barrier is proposed to make the SrO layer free of contaminations. Time of flight-secondary ion mass spectrometry (TOF-SIMS) analysis shows the diffusion of impurities, like Na and K, can be effectively blocked while a new SrO layer is formed on top of the MgO layer. This structure shows that high Xe gases can be used to improve the luminous efficacy 2.3 times and decrease the voltage margin more than 10 V compared to the conventional PDP using Ne-Xe 15%. The aging time was also significantly decreased to 3-4 h

Sparse Channel Estimation in Wideband Systems with Geometric Sequence Decomposition

The sparsity of multipaths in the wideband channel has motivated the use of compressed sensing for channel estimation. In this letter, we propose a different approach to sparse channel estimation. We exploit the fact that $L$ taps of channel impulse response in time domain constitute a non-orthogonal superposition of $L$ geometric sequences in frequency domain. This converts the channel estimation problem into the extraction of the parameters of geometric sequences. Numerical results show that the proposed scheme is superior to existing algorithms in high signal-to-noise ratio (SNR) and large bandwidth conditions

Want-To vs. Have-To Socializations in Social Network Sites: Fear of Isolation, Jealousy, and Tie Strengths

As social network sites (SNS) expand the boundaries of one’s social life, we often observe encounters between two different types of motivations for socialization - I want-to socialize vs. I have-to socialize. SNS at present are considered commodities. People do not always start using SNS because they want to, but often because everyone else is using it; people do not wish to be isolated from social circles. This study aims to examine different types of user motivations in SNS and observe how these lead to actual socialization behaviours with different progress dynamics. We apply constraint- and dedication- based relationship framework to distinguish motivations and identify constructs for each motivation. We plan to collect data from one of the major SNS to validate how their socialization intentions are differently realized into actual behaviours. We develop a two-staged research model and this research-in-progress presents the result of the pilot study conducted for the first stage. We also discuss how the second stage of the study will be executed, and how it will benefit the related literature when the project is successfully completed

Geometric Sequence Decomposition with kk-simplexes Transform

This paper presents a computationally efficient technique for decomposing non-orthogonally superposed $k$ geometric sequences. The method, which is named as geometric sequence decomposition with $k$-simplexes transform (GSD-ST), is based on the concept of transforming an observed sequence to multiple $k$-simplexes in a virtual $k$-dimensional space and correlating the volumes of the transformed simplexes. Hence, GSD-ST turns the problem of decomposing $k$ geometric sequences into one of solving a $k$-th order polynomial equation. Our technique has significance for wireless communications because sampled points of a radio wave comprise a geometric sequence. This implies that GSD-ST is capable of demodulating randomly combined radio waves, thereby eliminating the effect of interference. To exemplify the potential of GSD-ST, we propose a new radio access scheme, namely non-orthogonal interference-free radio access (No-INFRA). Herein, GSD-ST enables the collision-free reception of uncoordinated access requests. Numerical results show that No-INFRA effectively resolves the colliding access requests when the interference is dominant

Spatially resolved penetration depth measurements and vortex manipulation in the ferromagnetic superconductor ErNi2B2C

We present a local probe study of the magnetic superconductor, ErNi$_2$B$_2$C, using magnetic force microscopy at sub-Kelvin temperatures. ErNi$_2$B$_2$C is an ideal system to explore the effects of concomitant superconductivity and ferromagnetism. At 500 mK, far below the transition to a weakly ferromagnetic state, we directly observe a structured magnetic background on the micrometer scale. We determine spatially resolved absolute values of the magnetic penetration depth $\lambda$ and study its temperature dependence as the system undergoes magnetic phase transitions from paramagnetic to antiferromagnetic, and to weak ferromagnetic, all within the superconducting regime. In addition, we estimate the absolute pinning force of Abrikosov vortices, which shows a position- and temperature dependence as well, and discuss the possibility of the purported spontaneous vortex formation

Gene Synthesis from Oligonucleotide Mixtures by Solid Phase PCR and Assembly PCR in a Microfluidic Chip System.

The conventional gene synthesis methods, chemical or PCR, usually require over 2 weeks because of the separate executions of the different procedures. An integrated microfluidic chip system was designed to reduce this processing time to only 2 days with much less reaction volumes, and experimental reagent and solvent requirements. This fast high throughput gene synthesis method considerably minimizes contamination and simplifies material handling procedures. Our overall aim in this project is using the above-mentioned advantages of this system to synthesize long genes of arbitrary sequence with high purity, and cut the lead times and cost per base from the current values by at least one order of magnitude. In order to do this, four different steps are included in the microfluidic chip system: oligonucleotide synthesis and amplification on solid phase, on-chip purification, long DNA assembly, and gene transformation. The designed oligonucleotides to form the long DNAs were synthesized via light-directed phosphoramidite chemistry, and amplified on solid phase. The amplified products were treated by on-surface hybridization using complementary probes to make single strands and purification. The purified oligonucleotides were assembled into long DNAs on chip, and amplified with polymerase chain reaction in a separate microfluidic chip chamber. Finally, the synthetic target gene was transformed on a chip for gene expression. Our results showed these individual steps in bringing the system capability to a simultaneous production level of tens of double stranded oligonucleotides of lengths ranging from 0.2 to 1.2 kb and the potential of microfluidic gene and protein synthesis system.Ph.D.Biomedical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/75828/1/woonghl_1.pd

Exploring the Critical Success Factors for Customer Relationship Management and Electronic Customer Relationship Management Systems

Both customer relationship management (CRM) and electronic customer relationship management (eCRM) systems have unique characteristics that support customer-business interactions and are linked to internal business processes and systems across different areas for operational and analytical purposes. Such characteristics may imply that different critical success factors are required for both to be successfully implemented. This exploratory study identifies the factors and the interrelationships associated with the success of CRM and eCRM, compares the differences between CRM and eCRM, and discusses the reasons of the differences. Since there are only a few cases of CRM or eCRM systems fully implemented across marketing, technology, people, and business processes, an exploratory multiple-case study is conducted. The current status of CRM research and future research direction are discussed

Examining Information Systems Infusion over the Routinization

Information systems (IS) infusion becomes important from the management perspective because organizations can leverage IS investment only at the IS infusion stage. The model for the stages of IS implementation explains that IS infusion can be achieved through IS routinization. This study examined how to achieve IS infusion through routinization based on application of the psychological empowerment theory and the unified theory of acceptance and use of technology (UTAUT), respectively. This study adds value to the IS literature by explaining how IS routinization leads to IS infusion and how their antecedents are different and related across the two stages. This study also provides guidance on how organizations can promote IS infusion beyond IS routinization, which then helps organizations leverage their IS investments