Khan, Hafiz Mohammad Rafiqullah;Ibrahimou, Boubakari;Saxena, Anshul;Gabbidon, Kemesha;Abdool-Ghany, Faheema;Ramamoorthy, Venkataraghavan;Ullah, Duff;Stewart, Tiffanie Shauna-Jeanne
Asian Pacific Journal of Cancer Prevention
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v.15
no.19
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pp.8371-8376
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2014
Background: The use of statistical methods has become an imperative tool in breast cancer survival data analysis. The purpose of this study was to develop the best statistical probability model using the Bayesian method to predict future survival times for the black non-Hispanic female breast cancer patients diagnosed during 1973-2009 in the U.S. Materials and Methods: We used a stratified random sample of black non-Hispanic female breast cancer patient data from the Surveillance Epidemiology and End Results (SEER) database. Survival analysis was performed using Kaplan-Meier and Cox proportional regression methods. Four advanced types of statistical models, Exponentiated Exponential (EE), Beta Generalized Exponential (BGE), Exponentiated Weibull (EW), and Beta Inverse Weibull (BIW) were utilized for data analysis. The statistical model building criteria, Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC), and Deviance Information Criteria (DIC) were used to measure the goodness of fit tests. Furthermore, we used the Bayesian approach to obtain the predictive survival inferences from the best-fit data based on the exponentiated Weibull model. Results: We identified the highest number of black non-Hispanic female breast cancer patients in Michigan and the lowest in Hawaii. The mean (SD), of age at diagnosis (years) was 58.3 (14.43). The mean (SD), of survival time (months) for black non-Hispanic females was 66.8 (30.20). Non-Hispanic blacks had a significantly increased risk of death compared to Black Hispanics (Hazard ratio: 1.96, 95%CI: 1.51-2.54). Compared to other statistical probability models, we found that the exponentiated Weibull model better fits for the survival times. By making use of the Bayesian method predictive inferences for future survival times were obtained. Conclusions: These findings will be of great significance in determining appropriate treatment plans and health-care cost allocation. Furthermore, the same approach should contribute to build future predictive models for any health related diseases.
Investigations on the contaminated lands due to heavy metals from mining activities or hydrocarbons from oil spillage for example, should be planned based on specific fitness-for-purpose criteria(FFP criteria). A FFP criterion is site specific or varies with situation, based on which not only the data quality but also the decision quality can be determined. The limiting factors on the qualities can be, for example, the total budget for the investigation, regulatory guidance or expert's subjective fitness-for-purpose criterion. This paper deals with planning of investigation methods that can satisfy each suggested FFP criterion based on economic factors and the data quality. To this aim, a probabilistic loss function was applied to derive the cost effective investigation method that balances the measurement uncertainty, which estimates the degree of the data quality, with the decision quality. In addition, investigation planning methods when the objectives of investigations do not lie in the classification of the land but simply in producing the estimation of the mean concentration of the contaminant at the site(e.g. for the use in risk assessment), were also suggested. Furthermore, the efficient allocation of resources between sampling and analysis was also devised. These methods were applied to the two contaminated sites in the UK to test the validity of each method.
The low flow analysis is an important part in water resources engineering. Also, the results of low flow frequency analysis can be used for design of reservoir storage, water supply planning and design, waste-load allocation, and maintenance of quantity and quality of water for irrigation and wild life conservation. Especially, for identification of the uncertainty in frequency analysis, the Bayesian approach is applied and compared with conventional methodologies in at-site low flow frequency analysis. In the first manuscript, the theoretical background for the Bayesian MCMC (Bayesian Markov Chain Monte Carlo) method and Metropolis-Hasting algorithm are studied. Two types of the prior distribution, a non-data- based and a data-based prior distributions are developed and compared to perform the Bayesian MCMC method. It can be suggested that the results of a data-based prior distribution is more effective than those of a non-data-based prior distribution. The acceptance rate of the algorithm is computed to assess the effectiveness of the developed algorithm. In the second manuscript, the Bayesian MCMC method using a data-based prior distribution and MLE(Maximum Likelihood Estimation) using a quadratic approximation are performed for the at-site low flow frequency analysis.
In recent, the integrated water resources management should consider not only existing management objects such as water supply, power generation, and instream flows but also new management objects such as water quantity, water quality, and water habitats which management system is large and complex. Moreover, integrated basin plan or operation are needed for solving conflicts problems between basins and between water usages and to maximize water resources usages. To increase use of optimization method for actual operation and apply various objects, a reservoir operation rule was developed and the KModSim's hydrologic states for integrated water resources management were tested in this study. The simulation results show that the developed operation rules applied in hydrologic states good represent the actual storages of both the Yongdam and the Daecheong Reservoirs so, it is possible to improve the water allocation method usually used in the basin management and manage the integrated basin water resources if new operating rules are applied in optimized programming.
Massive broadcasting contents such as UHD(Ultra High Definition) TV which requires multi-channel capacity for transmission has been introduced in recent years. A transmission scheme with channel bonding has been considered for transmission of massive broadcasting contents. In HFC(Hybrid Fiber Coaxial) networks, DOCSIS 3.0(Data Over Cable Service Interface Specification 3.0) has already applied channel bonding schemes for up/downstream of data service. A method unlike DOCSIS 3.0 is required to introduce a channel bonding scheme in the broadcasting service having unidirectional transmission with a downstream. Since a massive broadcasting content requires several channels for transmission, VBR(Variable Bit Rate) transmission has been emerging for the bandwidth efficiency. In addition, research on channel allocation and resource scheduling is required to guarantee QoS(Quality of Service) for the broadcasting service based on VBR. In this paper, we propose a transmission method for mass broadcasting service in HFC network and show the UHD transmission simulator developed to evaluate the performance. In order to evaluate the performance, we define various scenarios. Using the simulator, we assess the possibility of channel bonding and VBR transmission for UHD broadcasting system to provide mass broadcasting service efficiently. The developed simulator is expected to contribute to the efficient transmission system development of mass broadcasting service.
Objective: Identification of the candidate genes that play key roles in phenotypic variations can provide new information about evolution and positive selection. Interleukin (IL)-32 is involved in many biological processes, however, its role for the immune response against various diseases in mammals is poorly understood. Therefore, the current investigation was performed for the better understanding of the molecular evolution and the positive selection of single nucleotide polymorphisms in IL-32 gene. Methods: By using fixation index ($F_{ST}$) based method, IL-32 (9375) gene was found to be outlier and under significant positive selection with the provisional combined allocation of mean heterozygosity and $F_{ST}$. Using nucleotide sequences of 11 mammalian species from National Center for Biotechnology Information database, the evolutionary selection of IL-32 gene was determined using Maximum likelihood model method, through four models (M1a, M2a, M7, and M8) in Codeml program of phylogenetic analysis by maximum liklihood. Results: IL-32 is detected under positive selection using the $F_{ST}$ simulations method. The phylogenetic tree revealed that goat IL-32 was in close resemblance with sheep IL-32. The coding nucleotide sequences were compared among 11 species and it was found that the goat IL-32 gene shared identity with sheep (96.54%), bison (91.97%), camel (58.39%), cat (56.59%), buffalo (56.50%), human (56.13%), dog (50.97%), horse (54.04%), and rabbit (53.41%) respectively. Conclusion: This study provides evidence for IL-32 gene as under significant positive selection in goat.
KIPS Transactions on Software and Data Engineering
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v.5
no.3
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pp.155-164
/
2016
For frequency pattern analysis of large databases, the new tree-based frequency pattern analysis algorithm which can compensate for the disadvantages of the Apriori method has been variously studied. In frequency pattern tree, the number of nodes is associated with memory allocation, but also affects memory resource consumption and processing speed of the growth. Therefore, reducing the number of nodes in the tree is very important in the frequency pattern mining. However, the absolute criteria which need to order the transaction items for construction frequency pattern tree has lowered the compression ratio of the tree nodes. But most of the frequency based tree construction methods adapted the absolute criteria. FP-tree is typically frequency pattern tree structure which is an extended prefix-tree structure for storing compressed frequent crucial information about frequent patterns. For construction the tree, all the frequent items in different transactions are sorted according to the absolute criteria, frequency descending order. CanTree also need to absolute criteria, canonical order, to construct the tree. In this paper, we proposed a novel frequency pattern tree construction method that does not use the absolute criteria, IRFP-tree algorithm. IRFP-tree(Intersection Rule based FP-tree). IRFP-tree is constituted with the new paradigm of the intersection rule without the use of the absolute criteria. It increased the compression ratio of the tree nodes, and reduced the tree construction time. Our method has the additional advantage that it provides incremental mining. The reported test result demonstrate the applicability and effectiveness of the proposed approach.
Up to date, the economic feasibility analysis on land consolidation and on-farm development projects were mainly depended upon the direct benefits from market value of project outputs. Therefore the projects were neglected in allocation of the government's financial funds and loans on account of undervaluation of the project benefits including socio-economic and environmental values of the projects. Accordingly the Extended Benefit Cost Analysis Method should be adapted to cover not only the benefits such as non-market values of environmental functions of the projects and but also the economic market values of the project outputs. The main objectives of this study is (1) to provision of the guideline for economic feasibility analysis based on the IBRD and ADB guidelines, (2) to estimate the benefits such as Productivity increase effect, labor saving effect, off-farm income increase effect during off-farm season, saving of O&M cost of farm mechanization, enhance of farmer's public health, increase of environmental public function of paddy fields, effect of food security and establishment of peaceful and uncontroversial rural society by implementing the land consolidation and on-farm development, (3) to introduce the newly adapted analytical method as the extended benefit cost analysis which could make possible the analysis of non-market goods such as the food security value and the environmental public value of paddy fields. To carry out the study, the publication on the guideline for economic analysis of agricultural projects were reviewed and consulted and for the post evaluation of the land consolidation and on-farm development project, field survey in Jeongja area were made for the feasibility study of the project by new method. According to the initial project plan, Jeongja land consolidation and on-farm development project has 96ha of benefit area and the project was started in 1989 and completed in the spring, 1990. The total project costs were amounted to 1,052 million won and the annual project benefits were estimated at 135.4 million in 1989 constant market prices. On the other hand, the newly estimated project benefits as a part of post evaluation of the project were amounted to 602.1 million won including all the benefits from the market and non-market commodities of the project as mentioned above column. The original IRP(Internal rate of return) of the project was estimated at 15.81%. On the other hand, the IRR of the post evaluation of the project was amounted to 16.83%. In case of including the benefit from the environment public function of paddy field, the SRR(Social Rate of Return) was reached to 38.81% and when we added the benefit from food security of the project, the SRR showed very high rate as 46.41%. In conclusion, the project were verified socio-economically feasible and environmentally sustainable considering the above decision making criteria.
The objective of the study is to develop a reservoir optimal operation model and to suggest the appropriate amount of additional water supply and optimal operation rule. The model uses multiple objective function and a global search method, SCE-UA method. The objective function is set up to maintain the storage at target level, to satisfy the water demand, and to maximize the hydropower product. To evaluate the model's applicability, the model was applied for allocating the optimal water depending on storage level changes of Seomjin dam. The results comparing optimal operation and historical data showed that hydropower product increased from $-2.29\%$ to $14.51\%$, $-5.94\%$ to $3.98\%$, and $-0.43\%$ to $6.35\%$ with varying target levels in wet, dry, and normal period, respectively. Also, The model was applied for assessing water supply capacity of Seomjin dam to satisfy increasing water demand. The dam was operated by the model on consideration of downstream flow as 0.17, 0.50, 0.70, 1.0, 1.5, and $3.0\;m^3/sec$. The results showed that in case of operating the dam with downstream flow less than $0.70\;m^3/sec$ and with target water level lower than 194.0 m, hydropower product was more than the historical operation data and existing amount of water supply was less influenced.
This paper introduces a risk graph which is one method for determining the SIL as a measure of the effectiveness of signaling system. The purpose of this research is to make up for the weakness of the qualitative determination, which has input value ambiguity and a boundary problem in the SIL range. The fuzzy input valuable consists of consequence, exposure, avoidance and demand rate. The fuzzy inference produces forty eight fuzzy rule by adapting the calibrated risk graph in the IEC 61511. The Max-min composition is utilized for the fuzzy inference. The result of the fuzzy inference is the fuzzy value. Therefore, using the de-fuzzification method, the result should be converted to a crisp value that can be utilized for real projects. Ultimately, the safety requirement for hazard is identified by proposing a SIL result with a tolerable hazard rate. For the validation the results of the proposed method, the fuzzy risk graph model is compared with the safety analysis of the signaling system in CENELEC SC 9XA WG A10 report.
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