Optimum Quality Level （OQL） ——The Main Proposition of Quality Economics

This paper discusses the Optimum Quality Level （OQL） controlling under the situation of competition and monopoly. While analyzing traditional OQL, we propose a new concept-Opportunity Revenue （OR）-to analyze the principle how enterprise pursues excellent quality to develop quality competition for OR. We further discuss how to decide Optimum Quality in monopoly market.

Optimal quality level,order quantity and selling price for the retailer in a two-level supply chain

For a classical order quantity/pricing problem,we present a geometric programming(GP)approach to find the optimal selling price,order quantity and quality level to maximize the profit for the retail firm.Traditional models such as EOQ are not able to handle the nonlinearity of costs and demand.We adopt the GP approach and make a proper transformation of the model so as to solve this classical problem and obtain the global optimal solution.In addition to the optimal solutions,we also perform a sensitivity analysis.The study shows once more that GP is an excellent approach when decision variables interact in a nonlinear,especially exponential manner.

A transcriptome-based analysis reveals functional differences among Dendrobium officinale Kimura&Migo species from different growing regions and with different quality levels

Dendrobium officinale Kimura&Migo(D.officinale)is a common,high medicinal value food and herbal medicine used in the treatment of yin-deficient diseases.Adulterants obtained with similar inexpensive species of Dendrobium plants are available in the market.However,Dendrobium species with different quality levels or from different regions as well as analogous species have a similar appearance,which makes the discrimination of Dendrobium species difficult.Reliable objective methods for authenticating D.officinale are lacking.Here,samples of Dendrobium officinale Kimura&Migo(D.officinale)from two regions with three quality levels and sample of the analogous species Dendrobium compactum Rolfe ex W.Hackett(D.compactum)were subjected to genome-wide biological response fingerprinting(BioReF)in RAW264.7 cells by RNA sequencing.The biological pathways affected by these samples could distinguish D.officinale from D.compactum.The high-quality D.officinale samples from Yunnan exhibited the strongest inhibition of lipopolysaccharide(LPS)induced inflammatory genes and pathways,followed by samples from Myanmar.The medium-and low-quality samples from Yunnan exhibited weaker effects,and D.compactum exerted mild effects.The RNA sequencing results were strengthened by the results from analyses of the expression of the inflammation-related genes Il6,Ccl5,and Cox2 and the production of nitric oxide.Thus,transcriptomic profiling can be used to evaluate the quality of D.officinale and distinguish its origin.

Imagery Data Quality of ZY Satellite Reached International Level

The in-orbit commissioning of ZY-1 02C satellite is proceeding smoothly. According to the relevant experts in this field, the imagery quality of the satellite has reached or nearly reached the level of international satellites of the same kind. ZY-1 02C satellite and ZY-3 satellite were successfully launched on December 22, 2011 and January 9, 2012 respectively. China Centre for Resources Satellite Data andApplication (CRSDA) was responsible for the building of a ground

A Novel Multiple Dependent State Sampling Plan Based on Time Truncated Life Tests Using Mean Lifetime

The design of a new adaptive version of the multiple dependent state(AMDS)sampling plan is presented based on the time truncated life test under the Weibull distribution.We achieved the proposed sampling plan by applying the concept of the double sampling plan and existing multiple dependent state sampling plans.A warning sign for acceptance number was proposed to increase the probability of current lot acceptance.The optimal plan parameters were determined simultaneously with nonlinear optimization problems under the producer’s risk and consumer’s risk.A simulation study was presented to support the proposed sampling plan.A comparison between the proposed and existing sampling plans,namely multiple dependent state(MDS)sampling plans and a modified multiple dependent state(MMDS)sampling plan,was considered under the average sampling number and operating characteristic curve values.In addition,the use of two real datasets demonstrated the practicality and usefulness of the proposed sampling plan.The results indicated that the proposed plan is more flexible and efficient in terms of the average sample number compared to the existing MDS and MMDS sampling plans.

An Optimal Resource Provision Policy in Cloud Computing Based on Customer Profiles

Conventional resource provision algorithms focus on how to maximize resource utilization and meet a fixed constraint of response time which be written in service level agreement（SLA）.Unfortunately,the expected response time is highly variable and it is usually longer than the value of SLA.So,it leads to a poor resource utilization and unnecessary servers migration.We develop a framework for customer-driven dynamic resource allocation in cloud computing.Termed CDSMS（customer-driven service manage system）,and the framework’s contributions are twofold.First,it can reduce the total migration times by adjusting the value of parameters of response time dynamically according to customers’profiles.Second,it can choose a best resource provision algorithm automatically in different scenarios to improve resource utilization.Finally,we perform a serious experiment in a real cloud computing platform.Experimental results show that CDSMS provides a satisfactory solution for the prediction of expected response time and the interval period between two tasks and reduce the total resource usage cost.