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Elasticity Analysis of Hierarchical Road Network Performance Based on Modified Logit Models
Minghua Zeng,Ziwen Ling,Bing Zhang,Xiyan Huang 대한토목학회 2018 KSCE JOURNAL OF CIVIL ENGINEERING Vol.22 No.10
This paper investigates the impact of Variable Message Sign (VMS), stochasticity and hierarchy on the performance of a road network in the context of four typical Logit model types. These models are multinomial Logit (MNL), C-Logit (CL), Path Size Logit (PSL) and Cross-nested Logit (CNL). We quantify the road hierarchy and use the quantified hierarchy to calculate generalized path costs. Then, VMS information is quantified and integrated with the hierarchical property to calculate road “length. Furthermore, these calculation methods are applied to propose modified versions of the MNL, CL, PSL and CNL. Numerical calculations produce negative values of the dispersion elasticity and hierarchical elasticity of total travel time costs obtained from each Logit model. The results also show that the dispersion parameter, hierarchical structure and VMS information have significant and different impacts on the elasticity. The quantitative interactions among these factors, models and performance are practically useful for network design and management.
Opportunistic Beamforming Communication With Throughput Analysis Using Asymptotic Approach
Minghua Xia,Yuanping Zhou,Ha, J.,Hyun Kyu Chung IEEE 2009 IEEE Transactions on Vehicular Technology VT Vol.58 No.5
<P>The opportunistic beamforming system (OBS) is currently receiving much attention in the field of downlink beamforming due to its simple random beamforming, low feedback complexity, and same throughput scaling obtained with perfect channel-state information using dirty paper coding at the transmitter. In this paper, we focus on its closed-form throughput evaluation over Rayleigh fading channels, based on the asymptotic theory of extreme order statistics. First, the throughput of a single-beam OBS is investigated, and an analytical solution tighter than the previously reported one is derived. Then, the asymptotic throughput bounds on a multibeam OBS are presented, and also, our analytical expression is shown to be very tight with the simulation results even with fewer users. After that, we argue that the reported conclusion that the single-beam OBS is much preferable to the multibeam OBS in the high-signal-to-noise-ratio (SNR) regime is inaccurate, but that, instead, it is satisfied only when the number of users is very small, due to its limited multiuser diversity gain. Finally, we show that four transmit beams is the most preferable in the multibeam OBS with a large number of users and moderate SNR, which arrives at the tradeoff between increasing spatial multiplexing gain and disappearing multiuser diversity gain.</P>
Feature Extraction via Sparse Difference Embedding (SDE)
( Minghua Wan ),( Zhihui Lai ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.7
The traditional feature extraction methods such as principal component analysis (PCA) cannot obtain the local structure of the samples, and locally linear embedding (LLE) cannot obtain the global structure of the samples. However, a common drawback of existing PCA and LLE algorithm is that they cannot deal well with the sparse problem of the samples. Therefore, by integrating the globality of PCA and the locality of LLE with a sparse constraint, we developed an improved and unsupervised difference algorithm called Sparse Difference Embedding (SDE), for dimensionality reduction of high-dimensional data in small sample size problems. Significantly differing from the existing PCA and LLE algorithms, SDE seeks to find a set of perfect projections that can not only impact the locality of intraclass and maximize the globality of interclass, but can also simultaneously use the Lasso regression to obtain a sparse transformation matrix. This characteristic makes SDE more intuitive and more powerful than PCA and LLE. At last, the proposed algorithm was estimated through experiments using the Yale and AR face image databases and the USPS handwriting digital databases. The experimental results show that SDE outperforms PCA LLE and UDP attributed to its sparse discriminating characteristics, which also indicates that the SDE is an effective method for face recognition.
Wang, Minghua,Zhang, Chen,Lee, Jae-Seong American Chemical Society 2018 Environmental science & technology Vol.52 No.3
<P>In this study, the copepod <I>Tigriopus japonicus</I> was exposed to different cadmium (Cd) treatments (0, 2.5, 5, 10, and 50 μg/L in seawater) for five generations (F0-F4), followed by a two-generation (F5-F6) recovery period in clean seawater. Six life-history traits (survival, developmental time of nauplius phase, developmental time to maturation, number of clutches, number of nauplii/clutch, and fecundity) were examined for each generation. Metal accumulation was also analyzed for generations F0-F6. Additionally, proteome profiling was performed for the control and 50 μg/L Cd-treated F4 copepods. In F0-F4 copepods, Cd accumulated in a concentration-dependent manner, prolonging the development of the nauplius phase and maturation and reducing the number of nauplii/clutch and fecundity. However, during F5-F6, Cd accumulation decreased rapidly, and significant but subtle effects on growth and reproduction were observed only for the highest metal treatment at F5. Proteomic analysis revealed that Cd treatment had several toxic effects including depressed nutrient absorption, dysfunction in cellular redox homeostasis and metabolism, and oxidative stress, resulting in growth retardation and reproduction limitation in this copepod species. Taken together, our results demonstrate the relationship between molecular toxicity responses and population-level adverse outcomes in <I>T. japonicus</I> under multigenerational Cd exposure.</P> [FIG OMISSION]</BR>