Insiders' Hedging for Jump Diffusion Processes with Applications to Index Tracking

The hedging problem for insiders is very important in the financial market.The locally risk minimizing hedging was adopted to solve this problem.Since the market was incomplete,the minimal martingale measure was chosen as the equivalent martingale measure.By the F-S decomposition,the expression of the locally risk minimizing strategy was presented.Finally,the local risk minimization was applied to index tracking and its relationship with tracking error variance (TEV)-minimizing strategy was obtained.

Evaluation of the Customer Satisfaction Index for Wellhead Blowout Preventers of China’s Petroleum Industry——A new method based on PLS

This paper establishes an evaluation model of the customer satisfaction index for the wellhead blowout preventers of China＇s petroleum industry based on evaluation models of the customer satisfaction index at home and aboard, and by considering the consuming situation in China and the features of the China＇s petroleum industry. For the existence of： （1） multiple correlations among the factors in the model; （2） the variables need to be explained, but that are hard to observe; （3） the customer satisfaction degree of observation variables appears the shape of skewness or two or three peaks, the correlations between the satisfaction index and its factors cannot be described by common multiple regression. This paper uses a partial least squares （PLS） method based on principal components and typical correlative analysis to solve the problem. When PLS is used in the model of the customer satisfaction index of the wellhead blowout preventers, the latent variables and the explanation degree coefficient of the manifest variable to the corresponding latent variables are estimated by PLS path analysis, and the influencing coefficient among the latent variables in the model is estimated by PLS regression analysis. PLS is also be used to calculate and analyze the model and disclose the correlations among the structural variables as well as the correlation between structural variables and its corresponding observation variables, evaluating results of which provide useful information for petroleum industry to improve the product quality and to the enhancement of the customer satisfaction to the product.

Determination of geological strength index of jointed rock mass based on image processing

The geological strength index(GSI) system,widely used for the design and practice of mining process,is a unique rock mass classification system related to the rock mass strength and deformation parameters based on the generalized Hoek-Brown and Mohr-Coulomb failure criteria.The GSI can be estimated using standard chart and field observations of rock mass blockiness and discontinuity surface conditions.The GSI value gives a numerical representation of the overall geotechnical quality of the rock mass.In this study,we propose a method to determine the GSI quantitatively using photographic images of in situ jointed rock mass with image processing technology,fractal theory and artificial neural network(ANN).We employ the GSI system to characterize the jointed rock mass around the working in a coal mine.The relative error between the proposed value and the given value in the GSI chart is less than 3.6%.

Development of index system for inherently safer process design using an integrated approach

With a growing population, an increasing number of petrochemical facilities are built with larger capacity and more complexity, which pose a great risk to assets, community and environment. The value of inherently safer design is recognized with time by all stakeholders, and an effective tool is needed to evaluate and compare inherent safety of alternative technologies. This study developed a safety index to evaluate existing technologies for their safety levels and guide inherently safer design. The Integrated Risk-based Safety Index(IRSI) was developed based on a comprehensive review of petrochemical processes, incident cases from Sinopec and US Chemical Safety Board, and existing safety index systems. The IRSI included all major hazards, including fire, explosion,toxic release, dust explosion, physical explosion, and runaway. Also, the integrated life cycle approach considered chemical hazards, equipment failure rates and safety measures in this risk-based index. Advanced modeling techniques, PHAST simulation and Neural Network, were used in the development of three novel sub-indices in the projects, fire, explosion and toxic release. The index system could be easily incorporated into a user friendly tool for the ease of application. A case study of hydrogen dioxide was conducted using the IRSI, which showed its capability for evaluating the safety level of process facilities.

Multivariate Statistical Process Monitoring and Control: Recent Developments and Applications to Chemical Industry

Multivariate statistical process monitoring and control (MSPM&C) methods for chemical process monitoring with statistical projection techniques such as principal component analysis (PCA) and partial least squares (PLS) are surveyed in this paper. The four-step procedure of performing MSPM&C for chemical process, modeling of processes, detecting abnormal events or faults, identifying the variable(s) responsible for the faults and diagnosing the source cause for the abnormal behavior, is analyzed. Several main research directions of MSPM&C reported in the literature are discussed, such as multi-way principal component analysis (MPCA) for batch process, statistical monitoring and control for nonlinear process, dynamic PCA and dynamic PLS, and on-line quality control by inferential models. Industrial applications of MSPM&C to several typical chemical processes, such as chemical reactor, distillation column, polymerization process, petroleum refinery units, are summarized. Finally, some concluding remarks and future considerations are made.

Response of Freezing/Thawing Indexes to the Wetting Trend under Warming Climate Conditions over the Qinghai–Tibetan Plateau during 1961–2010:A Numerical Simulation

Since the 1990s,the Qinghai–Tibetan Plateau(QTP)has experienced a strikingly warming and wetter climate that alters the thermal and hydrological properties of frozen ground.A positive correlation between the warming and thermal degradation in permafrost or seasonally frozen ground(SFG)has long been recognized.Still,a predictive relationship between historical wetting under warming climate conditions and frozen ground has not yet been well demonstrated,despite the expectation that it will become even more important because precipitation over the QTP has been projected to increase continuously in the near future.This study investigates the response of the thermal regime to historical wetting in both permafrost and SFG areas and examines their relationships separately using the Community Land Surface Model version 4.5.Results show that wetting before the 1990s across the QTP mainly cooled the permafrost body in the arid and semiarid zones,with significant correlation coefficients of 0.60 and 0.48,respectively.Precipitation increased continually at the rate of 6.16 mm decade–1 in the arid zone after the 1990s but had a contrasting warming effect on permafrost through a significant shortening of the thawing duration within the active layer.However,diminished rainfall in the humid zone after the 1990s also significantly extended the thawing duration of SFG.The relationship between the ground thawing index and precipitation was significantly negatively correlated(−0.75).The dual effects of wetting on the thermal dynamics of the QTP are becoming critical because of the projected increases in future precipitation.

SLC-index: A scalable skip list-based index for cloud data processing

Due to the increasing number of cloud applications,the amount of data in the cloud shows signs of growing faster than ever before.The nature of cloud computing requires cloud data processing systems that can handle huge volumes of data and have high performance.However,most cloud storage systems currently adopt a hash-like approach to retrieving data that only supports simple keyword-based enquiries,but lacks various forms of information search.Therefore,a scalable and efficient indexing scheme is clearly required.In this paper,we present a skip list-based cloud index,called SLC-index,which is a novel,scalable skip list-based indexing for cloud data processing.The SLC-index offers a two-layered architecture for extending indexing scope and facilitating better throughput.Dynamic load-balancing for the SLC-index is achieved by online migration of index nodes between servers.Furthermore,it is a flexible system due to its dynamic addition and removal of servers.The SLC-index is efficient for both point and range queries.Experimental results show the efficiency of the SLC-index and its usefulness as an alternative approach for cloud-suitable data structures.

A method for improving graph queries processing using positional inverted index (P.I.I) idea in search engines and parallelization techniques

The idea of positional inverted index is exploited for indexing of graph database. The main idea is the use of hashing tables in order to prune a considerable portion of graph database that cannot contain the answer set. These tables are implemented using column-based techniques and are used to store graphs of database, frequent sub-graphs and the neighborhood of nodes. In order to exact checking of remaining graphs, the vertex invariant is used for isomorphism test which can be parallel implemented. The results of evaluation indicate that proposed method outperforms existing methods.

An Improved PLS (IPLS) Method Utilizing Local Standardization Strategy for Multimode Process Monitoring

Complex industrial process often contains multiple operating modes, and the challenge of multimode process monitoring has recently gained much attention. However, most multivariate statistical process monitoring (MSPM) methods are based on the assumption that the process has only one nominal mode. When the process data contain different distributions, they may not function as well as in single mode processes. To address this issue, an improved partial least squares (IPLS) method was proposed for multimode process monitoring. By utilizing a novel local standardization strategy, the normal data in multiple modes could be centralized after being standardized and the fundamental assumption of partial least squares (PLS) could be valid again in multimode process. In this way, PLS method was extended to be suitable for not only single mode processes but also multimode processes. The efficiency of the proposed method was illustrated by comparing the monitoring results of PLS and IPLS in Tennessee Eastman(TE) process.

Assessment and Application of Beach Quality Based on Analytic Hierarchy Process in Yangkou Beach, Qingdao

The whole-beach quality assessment is the basis of building and preserving beautiful beaches.The beach quality assessment index system and assessment standard have been established based on the attributes of beaches(including the width,slope,landform,and types),sorting coefficient,and softness degree of surface sediment.The assessment weight of each index for quality evaluation was analyzed using the analytic hierarchy process,and comprehensive scores of selected beach profiles were calculated in accordance with the light assessment standard.A beach quality evaluation model based on index weight and scores was established in this paper.The factors of 12 profiles of Yangkou Beach in Qingdao City were surveyed to carry out a quality assessment,and the comprehensive scores of each profile were calculated in accordance with the evaluation model.The results showed that the quality of Yangkou Beach can be divided into four ratings:excellent,good,medium,and poor.The excellent-quality area includes a wide and flat dry beach zone and soft,flat,and clean intertidal and subtidal zones covered with well-sorted fine sand,and leisure sports,such as volleyball,running,and swimming,are suitable for tourists.The good-quality area features a slightly narrow and dry beach zone,moderately soft and uneven intertidal and subtidal zones covered with fine sand and a small tidal gully,and a small amount of foreign matter;leisure sports,such as walking and running,are suitable for tourists.This study recommends the building of fixed drainage ditches or underground culverts to reduce the tidal gully.The medium-quality area consisted of a narrow and dry beach zone,moderately soft and uneven intertidal and subtidal zones covered by poorly sorted medium sand,a tide ditch,and a small amount of foreign matter.In this area,walking is suitable for tourists.Sand should be supplemented in the intertidal zone.The poor-quality area contained a very narrow and dry beach zone covered with poor-sorted gravel,a very chaotic intertidal zone with a considerable amount of foreign matters,such as bricks and rocks,wide tidal ditches,and an uneven subtidal zone with some reefs;leisure sports are unsuitable here.Thus,foreign matter and reefs should be removed,and the dry beach zone should be supplemented with sand.Therefore,the beach quality assessment is a very useful tool for building beautiful beaches.

A Multivariate Process Capability Index

Process capability indices have been widely used in the manufacturing industry,providing numerical measures on process precision,process accuracy,and process performance.Capability measures for processes with a single characteristic have been investigated extensively.However,capability measures for processes with multiple characteristics are comparatively neglected. In this paper,inspired by the approach and model of process capability index investigated by K.S.Chen et al.(2003) and A.B. Yeh et al.(1998),a note model of multivariate process capability index based on non-conformity is presented.As for this index, the data of each single characteristic don’t require satisfying normal distribution,of which its computing is simple and particioners will not fell too theoretical.At last the application analysis is made.

Modified Multivariate Process Capability Index Using Principal Component Analysis

The existing research of process capability indices of multiple quality characteristics mainly focuses on nonconforming of process output, the concept development of tmivariate process capability indices, quality loss function and various comprehensive evaluation methods. The multivariate complexity increases the computation difficulty of multivariate process capability indices（MPCI）, which makes them hard to be used in practice. In this paper, a new PCA-based MPCI approach is proposed to assess the production capability of the processes that involve multiple product quality characteristics. This approach first transforms the original quality variables into standardized normal variables. MPCI measures are then provided based on the Taam index. Moreover, the statistical properties of these MPCIs, such as confidence intervals and lower confidence bound, are given to let the practitioners understand the capability indices as random variables instead of deterministic variables. A real manufacturing data set and a synthetic data set are used to demonstrate the effectiveness of the proposed method. An implementation procedure is also provided for quality engineers to apply our MPCI approach in their manufacturing processes. The case studies demonstrate the effectiveness and feasibility of this new kind of MPCI, which is easier to be used in production practice. The proposed research provides a novel approach of MPCI calculation.

Extracting the Influential Commodities in Stochastic Model of Simple Laspeyre Price Index Numbers with AR(2) Errors

This paper, on the first hand, deals with the problem of estimation of Laspeyre price index number when the errors are assumed to be generated from AR(2) process. The general expression of hat matrix and DFBETA measure to find the influential consumer commodities in stochastic Laspeyre price model with AR(2) errors are developed on the other. The hat values show the noteworthy findings that the corresponding weights of consumer items have large influence on the parameter estimates for simple Laspeyre price index number and are not affected by the parameter of autoregressive process of order two. While, DFBETA measures are the functions of both weights and autocorrelation parameters. Lastly, an example is presented with reference to price data of Pakistan, and shows its practical importance in financial time series.

Asymptotic Evaluations of the Stability Index for a Markov Control Process with the Expected Total Discounted Reward Criterion

In this work, for a control consumption-investment process with the discounted reward optimization criteria, a numerical estimate of the stability index is made. Using explicit formulas for the optimal stationary policies and for the value functions, the stability index is explicitly calculated and through statistical techniques its asymptotic behavior is investigated (using numerical experiments) when the discount coefficient approaches 1. The results obtained define the conditions under which an approximate optimal stationary policy can be used to control the original process.

Effects of Process and Storage Temperature on Browning Index, Furosine, and HMF of Aseptic Cold Break Tomato Paste during Storage Time

Effects of process and storage temperature on concentration of Maillard compounds in aseptic cold break tomato paste were evaluated during 12 months of storage time. Cold break tomato paste was processed at 104 ℃ or 112℃, aseptically filled into 5 liter bags, and stored at 21 ℃ and 33 ℃. Level of Browning Index, Furosine, and HMF was monitored in the aseptic cold break tomato paste during the storage time. Browning Index, Furosine, and HMF significantly increased in the aseptic cold break tomato paste during storage at 33℃, and there was linear correlation between Browning Index and Furosine （or HMF）. At the lower storage temperature of 21℃, no significant increases were observed. Effects of the process temperature on Browning Index, Furosine, and HMF of aseptic cold break tomato paste were less significant than the storage temperature.

Computing Method of Multivariate Process Capability Index Based on Normalized Pretreatment

For the traditional multi-process capability construction method based on principal component analysis,the process variables are mainly considered,but not the process capability,which leads to the deviation of the contribution rate of principal component.In response to the question,this paper first clarifies the problem from two aspects:theoretical analysis and example proof.Secondly,aiming at the rationality of principal components degree,an evaluation method for pre-processing data before constructing MPCI using PCA is proposed.The pre-processing of data is mainly to standardize the specification interval of quality characteristics making the principal components degree more reasonable and optimizes the process capability evaluation method.Finally,the effectiveness and feasibility of the method are proved by an application example.

How can technology and efficiency alleviate the dilemma of economic growth and carbon emissions in China's industrial economy? A metafrontier decoupling decomposition analysis

This paper attempts to explore the decoupling relationship and its drivers between industrial economic increase and energy-related CO_(2) emissions(ICE). Firstly, the decoupling relationship was evaluated by Tapio index. Then, based on the DEA meta-frontier theory framework which taking into account the regional and industrial heterogeneity and index decomposition method, the driving factors of decoupling process were explored mainly from the view of technology and efficiency. The results show that during2000-2019, weak decoupling was the primary state. Investment scale expansion was the largest reason hindering decoupling process of industrial increase from ICE. Both energy saving and production technology achieved significant progress, which facilitated the decoupling process. Simultaneously, the energy technology gap and production technology gap among regions have been narrowed, and played a role in promoting decoupling process. On the contrary, both scale economy efficiency and pure technical efficiency have inhibiting effects on decoupling process. The former indicates that the scale economy of China's industry was not conducive to improve energy efficiency and production efficiency, while the latter indicates that resource misallocation problem may exist in both energy market and product market.

Effect of the Various Processed Food of the Far North Cameroon on the Glycemic Index

Metabolic Syndrome (MS) has reached a pandemic proportion and has an impact on the incidence and severity of cardiovascular pathologies. This study was conducted to evaluate the effect of different processed food commonly consumed in Maroua (Far North Region, Cameroon) on the Glycemic Index (GI). To ameliorate the follow up of MS and population’s nutrition education, a survey was conducted among 200 families. The ten most consumed meals were selected after a food survey among 200 families. The meals were mostly made of a vegetable soup associated to a high carbohydrate staple. Vegetables and cereals were processed according to the food survey results. Then, a food tolerance test was performed on 30 male volunteers living in the same region. Among them, 12 were selected with an average age of 28.25 and a mean BMI of 19.63. They were studied on separate occasions in the morning after an overnight fast. After fasting, blood glucose was taken before and (15, 30, 45, 60, 90 and 120 minutes) after eating a test meal compared to sucrose and glucose solution (33.33%) used as reference. Glycemic response curves were used to calculate the gi of each meal. Results show that GI of the tested meals varied significantly (p < 0.05) between 20 and 79. Red millet porridge with kelenkelen-beans (Cochorus oletorius-Vigna unguiculata) sauce and red millet porridge with kelenkelen-peanut (Cochorus oletorius-Arachis hypogea) sauce exhibited the lowest GI. The highest GI was observed in corn porridge associated with fresh okra (Hibuscus esculentus) or with tasba (Cassia tora)-okra-beans sauce.

A process monitoring method for autoregressive-dynamic inner total latent structure projection

As a dynamic projection to latent structures(PLS)method with a good output prediction ability,dynamic inner PLS(DiPLS)is widely used in the prediction of key performance indi-cators.However,due to the oblique decomposition of the input space by DiPLS,there are false alarms in the actual industrial process during fault detection.To address the above problems,a dynamic modeling method based on autoregressive-dynamic inner total PLS(AR-DiTPLS)is proposed.The method first uses the regression relation matrix to decompose the input space orthogonally,which reduces useless information for the predic-tion output in the quality-related dynamic subspace.Then,a vector autoregressive model(VAR)is constructed for the predic-tion score to separate dynamic information and static informa-tion.Based on the VAR model,appropriate statistical indicators are further constructed for online monitoring,which reduces the occurrence of false alarms.The effectiveness of the method is verified by a Tennessee-Eastman industrial simulation process and a three-phase flow system.

A preliminary site selection system for underground hydrogen storage in salt caverns and its application in Pingdingshan,China

Large‐scale underground hydrogen storage(UHS)provides a promising method for increasing the role of hydrogen in the process of carbon neutrality and energy transition.Of all the existing storage deposits,salt caverns are recognized as ideal sites for pure hydrogen storage.Evaluation and optimization of site selection for hydrogen storage facilities in salt caverns have become significant issues.In this article,the software CiteSpace is used to analyze and filter hot topics in published research.Based on a detailed classification and analysis,a“four‐factor”model for the site selection of salt cavern hydrogen storage is proposed,encompassing the dynamic demands of hydrogen energy,geological,hydrological,and ground factors of salt mines.Subsequently,20 basic indicators for comprehensive suitability grading of the target site were screened using the analytic hierarchy process and expert survey methods were adopted,which provided a preliminary site selection system for salt cavern hydrogen storage.Ultimately,the developed system was applied for the evaluation of salt cavern hydrogen storage sites in the salt mines of Pingdingshan City,Henan Province,thereby confirming its rationality and effectiveness.This research provides a feasible method and theoretical basis for the site selection of UHS in salt caverns in China.