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Search Results: 1 - 10 of 59094 matches for " Jin Zhou "
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Valuation of a Tranched Loan Credit Default Swap Index  [PDF]
Jin Liang, Yujing Zhou
Technology and Investment (TI) , 2011, DOI: 10.4236/ti.2011.24025
Abstract: This paper provides a methodology for valuing a Loan Credit Default Swap Index (LCDX) and its tranches involving both default and prepayment risks. The valuation is path dependence, where interest, default and prepayment rates are correlated stochastic processes following CIR processes. By Monte Carlo simulation, a numerical solution and team structure of tranched LCDX are obtained. Computing examples are provided.
Analyses and Numerical Modeling of Gravity Waves Generated by Flow over Nanling Mountains  [PDF]
Ziliang Li, Jin Zhou
Atmospheric and Climate Sciences (ACS) , 2014, DOI: 10.4236/acs.2014.42032
Abstract: Although there have been many observational and modeling studies of gravity waves excited by topograpghy, the detailed structure and its changes in real world are still poorly understood. The interaction of topography and background flow are described in details for a better understanding of the gravity waves observed by the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery over Nanling Mountains. The evolutionary process and spatial structure of gravity waves were investigated by using almost all available observational data, including MODIS satellite imagery, the Final Analyses (FNL) data issued by National Centers for Environmental Prediction (NCEP), the aerosol backscattering signal data from Lidar, the surface observational data and the sounding data of Nanling mountain regions. In order to study its development mechanism, choosing the initial sounding of Jiangxi Gaizhou station located in the upstream of Nanling regions, and using the Advanced Regional Prediction System (ARPS), the numerical simulation was performed. It is shown that the ARPS model reproduced the main features of gravity waves reasonably well, where the gravity waves and turbulent mixed layer are consistent with the satellite image and the aerosol backscattering signal from Lidar observation. It is well-known that gravity wave-induced turbulence and thus turbulent mixing could affect the local composition of chemical species, which plays a significant role in the formation of low visibility and precipitation associated with local orography.
Local Kernel Dimension Reduction in Approximate Bayesian Computation  [PDF]
Jin Zhou, Kenji Fukumizu
Open Journal of Statistics (OJS) , 2018, DOI: 10.4236/ojs.2018.83031
Abstract: Approximate Bayesian Computation (ABC) is a popular sampling method in applications involving intractable likelihood functions. Instead of evaluating the likelihood function, ABC approximates the posterior distribution by a set of accepted samples which are simulated from a generating model. Simulated samples are accepted if the distances between the samples and the observation are smaller than some threshold. The distance is calculated in terms of summary statistics. This paper proposes Local Gradient Kernel Dimension Reduction (LGKDR) to construct low dimensional summary statistics for ABC. The proposed method identifies a sufficient subspace of the original summary statistics by implicitly considering all non-linear transforms therein, and a weighting kernel is used for the concentration of the projections. No strong assumptions are made on the marginal distributions, nor the regression models, permitting usage in a wide range of applications. Experiments are done with simple rejection ABC and sequential Monte Carlo ABC methods. Results are reported as competitive in the former and substantially better in the latter cases in which Monte Carlo errors are compressed as much as possible.
Feasibility Study of Parameter Identification Method Based on Symbolic Time Series Analysis and Adaptive Immune Clonal Selection Algorithm  [PDF]
Rongshuai Li, Akira Mita, Jin Zhou
Open Journal of Civil Engineering (OJCE) , 2012, DOI: 10.4236/ojce.2012.24026
Abstract: The feasibility of a parameter identification method based on symbolic time series analysis (STSA) and the adaptive immune clonal selection algorithm (AICSA) is studied. Data symbolization by using STSA alleviates the effects of harmful noise in raw acceleration data. The effect of the parameters in STSA is theoretically evaluated and numerically verified. AICSA is employed to minimize the error between the state sequence histogram (SSH) that is transformed from raw acceleration data by STSA. The proposed methodology is evaluated by comparing it with AICSA using raw acceleration data. AICSA combining STSA is proved to be a powerful tool for identifying unknown parameters of structural systems even when the data is contaminated with relatively large amounts of noise.
Hybrid Methodology for Structural Health Monitoring Based on Immune Algorithms and Symbolic Time Series Analysis  [PDF]
Rongshuai Li, Akira Mita, Jin Zhou
Journal of Intelligent Learning Systems and Applications (JILSA) , 2013, DOI: 10.4236/jilsa.2013.51006

This hybrid methodology for structural health monitoring (SHM) is based on immune algorithms (IAs) and symbolic time series analysis (STSA). Real-valued negative selection (RNS) is used to detect damage detection and adaptive immune clonal selection algorithm (AICSA) is used to localize and quantify the damage. Data symbolization by using STSA alleviates the effects of harmful noise in raw acceleration data. This paper explains the mathematical basis of STSA and the procedure of the hybrid methodology. It also describes the results of an simulation experiment on a five-story shear frame structure that indicated the hybrid strategy can efficiently and precisely detect, localize and quantify damage to civil engineering structures in the presence of measurement noise.

Downlink Scheduling and Rate Capping for LTE-Advanced Carrier Aggregation  [PDF]
Mieszko Chmiel, Jin Shi, David X. Zhou
Communications and Network (CN) , 2013, DOI: 10.4236/cn.2013.53B2001
Abstract: Long Term Evolution (LTE) Carrier Aggregation (CA) was introduced by the Release-10 3GPP specifications. CA allows aggregation of up to 5 cells for a terminal; both downlink (DL) CA and uplink (UL) CA are supported by the 3GPP specifications. However, the first commercial deployments focus on the aggregation of two cells in the downlink. The benefits of LTE CA are increased terminal peak data rates, aggregation of fragmented spectrum and fast load balancing. In this paper, we analyze different strategies of DL scheduling for LTE CA including centralized, independent and distributed schedulers, we provide the corresponding simulation results considering UE data rate limitations and different traffic models. Also, we compare the performance of a single LTE carrier with LTE CA using the same total bandwidth.
Pseudo DNA Sequence Generation of Non-Coding Distributions Using Variant Maps on Cellular Automata  [PDF]
Jeffrey Zheng, Jin Luo, Wei Zhou
Applied Mathematics (AM) , 2014, DOI: 10.4236/am.2014.51018

In a recent decade, many DNA sequencing projects are developed on cells, plants and animals over the world into huge DNA databases. Researchers notice that mammalian genomes encoding thousands of large noncoding RNAs (lncRNAs), interact with chromatin regulatory complexes, and are thought to play a role in localizing these complexes to target loci across the genome. It is a challenge target using higher dimensional tools to organize various complex interactive properties as visual maps. In this paper, a Pseudo DNA Variant MapPDVM is proposed following Cellular Automata to represent multiple maps that use four Meta symbols as well as DNA or RNA representations. The system architecture of key components and the core mechanism on the PDVM are described. Key modules, equations and their I/O parameters are discussed. Applying the PDVM, two sets of real DNA sequences from both the sample human (noncoding DNA) and corn (coding DNA) genomes are collected in comparison with two sets of pseudo DNA sequences generated by a stream cipher HC-256 under different modes to show their intrinsic properties in higher levels of similar relationships among relevant DNA sequences on 2D maps. Sample 2D maps are listed and their characteristics are illustrated under a controllable environment. Various distributions can be observed on both noncoding and coding conditions from their symmetric properties on 2D maps.

Research on the Relationship between Enterprise Network Resources and Market Scope of Cross-Regional Integration: An Empirical Study under Condition of Market Segmentation in China  [PDF]
Guangyu Ye, Tiantian Jin, Yan Zhou
Open Journal of Business and Management (OJBM) , 2015, DOI: 10.4236/ojbm.2015.34039
Abstract: In order to survive in the fierce competition in Chinese market, Chinese companies gradually start to integrate the domestic market cross-regionally. Although the integration strategy has already become one of the important growth tactics, there are very few researches focused on enterprise network resources when discussed cross-regional integration, not to mention the special market environment in China—market segmentation. According to resource-based view and social network theory, we studied the relationship between enterprise network resources and the market scope of cross-regional integration. Taking Chinese market segmentation into consideration, we analyzed the moderating effect of institutional distance and entrepreneurial orientation. Based on empirical analysis of 439 valid questionnaires, we found that enterprise network resources had a positive effect on the market scope of cross-regional integration; and institutional distance moderated the correlation between network resources and market scope positively.
Study on the Role of Supersonic Nozzle in Fiber Laser Cutting of Stainless Steel  [PDF]
Yijun Zhou, Jilan Kong, Jin Zhang
Materials Sciences and Applications (MSA) , 2017, DOI: 10.4236/msa.2017.81006
Abstract: Striation-free laser cutting, especially for thick section steel, is hard to obtain due to several factors. The inside shape of the gas nozzle is considered to be one of the most vital factors in striation-free fiber laser cutting. 0.8 mm normal nozzle and a supersonic nozzle are used to cut 0.8 mm AISI316L stainless steel (022Cr17Ni12Mo2) separately. The orthogonal experiment takes nozzle standoff distance, cutting speed, Laser power and gas pressure as its impacting factors. The same orthogonal table is adopted in different condition, using normal nozzle and using supersonic nozzle. In the mean time, Ar gas is used as assisted cutting gas in the experiment. The data from this experiment show that supersonic nozzle seems to be a strong helper for fiber laser cutting. Feed rate’s effect seems stable and inconspicuous under the condition of using supersonic nozzle.
Valuation of Credit Default Swap with Counterparty Default Risk by Structural Model  [PDF]
Jin Liang, Peng Zhou, Yujing Zhou, Junmei Ma
Applied Mathematics (AM) , 2011, DOI: 10.4236/am.2011.21012
Abstract: This paper provides a methodology for valuing a credit default swap (CDS) with considering a counterparty default risk. Using a structural framework, we study the correlation of the reference entity and the counterparty through the joint distribution of them. The default event discussed in our model is associated to whether the minimum value of the companies in stochastic processes has reached their thresholds (default barriers). The joint probability of minimums of correlated Brownian motions solves the backward Kolmogorov equation, which is a two dimensional partial differential equation. A closed pricing formula is obtained. Numerical methodology, parameter analysis and calculation examples are implemented.
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