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Search Results: 1 - 10 of 4128 matches for " Prediction "
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The Golden Age for Pawnshops Current Social Factors that Drive their Success in the Mexican Market
Edly Mortera
School of Doctoral Studies Journal , 2012,
Abstract: Credit plays an important role in the world's finances, but what happens when it is impossible for a great part of the population to have access to it? Besides a mismanagement of personal finances, that have led to a continuous increase in performing loans and distressed assets; there are external social factors that prohibit consumers facing their obligations by basic financial instruments such as short time loans. When unexpected bills come up, these consumers often find themselves in a bind, and they must look to alternative products. In Mexico we have a potential market of 40 million people without access to the banking system and whose needs for flexible financial options are growing constantly. Today the banking industry serves only 20% of demand. Facing this scenario, and complimented by the factors discussed below, a huge opportunity arises for a last resort lender: The Pawn Shops.
Defect Prediction Leads to High Quality Product  [PDF]
Naheed Azeem, Shazia Usmani
Journal of Software Engineering and Applications (JSEA) , 2011, DOI: 10.4236/jsea.2011.411075
Abstract: Defect prediction is relatively a new research area of software quality assurance. A project team always aims to produce a quality product with zero or few defects. Quality of a product is correlated with the number of defects as well as it is limited by time and by money. So, defect prediction is very important in the field of software quality and software reliability. This paper gives you a vivid description about software defect prediction. It describes the key areas of software defect prediction practice, and highlights some key open issues for the future.
Prediction of Suitable Harvest Time in Aquaculture  [PDF]
Zhaotang Shang, Lin Cheng, Mengsen Luo, Lang He, Zhigang Lu
Natural Resources (NR) , 2013, DOI: 10.4236/nr.2013.42024

A model is provided to predict the prawn’s harvest in aquaculture through analytical research in agrometeorology, mathematical statistics, synoptic meteorology and et al. It is found out that the Benefit Analysis of the Best Harvest is one of the most ideal ways. The models for the breeding objects, climate prediction and analysis of market quotation should be set up and perfected continuously. Only when the dynamic numerical simulation of the growth is accurate and the short-term weather forecast and the market quotation are reliable, will the suitable harvest time be predicted precisely. We used to write this paper with the foundation on ideologies.

Mid Trimester Transvaginal Ultrasound Assessment of Cervix for Prediction of Primary Caesarean Section  [PDF]
Mamta Rath Datta, Shikha Parashar, Priyanka Mukherjee, Sarita Kumari, Ankush Nandkishor Raut
Open Journal of Obstetrics and Gynecology (OJOG) , 2015, DOI: 10.4236/ojog.2015.515121
Abstract: Objectives: To assess the role of mid-trimester transvaginal sonographic assessment of cervix in predicting the risk of primary cesarean section. Methods: Hundred pregnant women, who attended out-patient department of Tata Main Hospital for ante natal examination, from 1st December 2011 to 1st December 2012, were taken up for the study. Only those who had confirmed dates were included in the study. Transvaginal sonography was done at 18 - 26 week to measure cervical length. Parameters studied were gestational age at delivery, whether spontaneous or induced, duration of labor, pregnancy outcome and mode of delivery and indication for cesarean section. Results: Majority of LSCS were in the group with cervical length ≥4 cm (57.1%) with “p” value of <0.0001. Only 13.8% women who had vaginal delivery had cervical length ≥4 cm. Out of the 32 women with cervical length ≥4 cm, 26 (81.3%) required induction of labor and 10 (31.3%) delivered after 40 weeks. Mean cervical length for spontaneous onset of labor was 3.11 ± 0.85 cm and for induction of labor was 4.36 ± 1.11 cm (“p” value ≤ 0.001). Multiple logistic regression analysis was performed to study outcome variable of mode of delivery. Cervical length and induction to delivery interval were found to be independent predictor of mode of delivery. In the receiver operating characteristic (ROC) curve analysis, the best cut-off point for prediction of primary cesarean section was 40 mm for cervical length. Sensitivity, specificity, positive predictive value and negative predictive value of cervical length as a predictor of mode of delivery was 54.8%, 91.4%, 82.1% and 73.6% respectively. R2 (coefficient of determination) was 0.271. Conclusion: Transvaginal cervical length measurement at mid trimester can be used as a predictive tool to determine the risk of primary cesarean section as well as the need of induction of labor.
A New Prediction System of Sepsis: A Retrospective, Clinical Study  [PDF]
Enhe Liu, Zhinan Zheng, Qiuye Kou
Modern Research in Inflammation (MRI) , 2016, DOI: 10.4236/mri.2016.54007
Abstract: Objective: Analyzing 6 biomarkers, such as procalcitonin (PCT), C-reactive protein (CRP), fibrinogen (Fib), lactate concentration (Lac), D-dimer (D-d), neutrophil ratio (NEUT%) to figure out several sensitive indicators and establish a new prediction system of sepsis, which could achieve a higher sensitivity and specificity to predict sepsis. Methods: We collected 113 SIRS patients in ICU. According to their prognosis, all the patients were divided into two groups named sepsis and non-sepsis group according to the diagnostic criteria of sepsis. We recorded the general information and detected the plasma levels of the 6 biomarkers. Results: The plasma levels of NEUT% and Fib between the two groups had no significant difference. PCT had the highest prediction accuracy of sepsis compared with other biomarkers. A predictive model was established, in which Lac, PCT, CRP were enrolled. The final prediction model was: logit(P) = 0.314 + 0.105 × Lac(mmol/l) + 0.099 × PCT(ng/mL) + 0.012 ×
Comparison of Wheat Yield Simulated Using Three N Cycling Options in the SWAT Model  [PDF]
Elizabeth Brooke Haney, Richard Lee Haney, Michael James White, Jeffrey George Arnold
Open Journal of Soil Science (OJSS) , 2018, DOI: 10.4236/ojss.2018.88016
Abstract: The Soil and Water Assessment Tool (SWAT) model has been successfully used to predict alterations in streamflow, evapotranspiration and soil water; however, it is not clear how effective or accurate SWAT is at predicting crop growth. Previous research suggests that while the hydrologic balance in each watershed is accurately simulated with SWAT, the SWAT model over or under predicts crop yield relative to fertilizer inputs. The SWAT model now has three alternative N simulation options: 1) SWAT model with an added flush of N (SWAT-flush); 2) N routines derived from the CENTURY model (SWAT-C); and 3) a one-pool C and N model (SWAT-One). The objective of this study was to evaluate the performance of SWAT-flush, SWAT-C, and SWAT-One as they affect wheat yield prediction. Simulated yields were compared to wheat yields in a 28-year fertilizer/wheat yield study in Lahoma, OK. Simulated yields were correlated with actual 28-year mean yield; however, none of the available N cycling models predicted yearly yields. SWAT-C simulated average yields were closer than other N sub-models to average actual yield. Annually there was a stronger correlation between SWAT-flush and actual yields than the other submodels. However, none of the N-cycling routines were able to accurately predict annual variability in yield at any fertilizer rate. We found that SWAT-C or SWAT-flush are the most viable choices for accurately simulating long-term average wheat yields although annual variations in yield prediction should be taken into consideration. Further research is needed to determine the effectiveness of SWAT-C and SWAT-flush in determining average and annual yield in various farming regions and with numerous agronomic crops.
Intelligent HEV Fuzzy Logic Control Strategy Based on Identification and Prediction of Drive Cycle and Driving Trend  [PDF]
Limin Niu, Hongyuan Yang, Yuhua Zhang
World Journal of Engineering and Technology (WJET) , 2015, DOI: 10.4236/wjet.2015.33C032

Real-time drive cycles and driving trends have a vital impact on fuel consumption and emissions in a vehicle. To address this issue, an original and alternative approach which incorporates the knowledge about real-time drive cycles and driving trends into fuzzy logic control strategy was proposed. A machine learning framework called MC_FRAME was established, which includes two neural networks for self-learning and making predictions. An intelligent fuzzy logic control strategy based on the MC_FRAME was then developed in a hybrid electric vehicle system, which is called FLCS_MODEL. Simulations were conducted to evaluate the FLCS_MODEL using ADVISOR. The simulation results indicated that comparing with the default controller on the drive cycle NEDC, the FLCS_MODEL saves 12.25% fuel per hundred kilometers, with the HC emissions increasing by 22.7%, the CO emissions reducing by 16.5%, the NOx emissions reducing by 37.5% and with the PM emissions reducing by 12.9%. A conclusion can be drawn that the proposed approach realizes fewer fuel consumption and less emissions.

Forecast of China Population under Different Fertility Policy  [PDF]
Jun’e Liu, Lei Chai, Zina Xu
Open Journal of Social Sciences (JSS) , 2016, DOI: 10.4236/jss.2016.47031
Abstract: In this paper, we use queue elements prediction and forecasting software PADIS-INT, set three different fertility programs, and predict China’s total population and the trends of population structural change in 2015-2050, based on the fifth and sixth national census data. The results show that since implementation of the two-child family planning policy, the aging trend of the population structure will be significantly improved, and after 2030 our population structure will be gradually younger. In view of the problem of population sex ratio imbalance, we verified it, and the results showed that by 2020 there will be a bachelor phenomenon, but the number did not report as much. Finally, we gave a brief summary and recommendations for our studies.
Research of Neuron Growth Prediction and Influence of Its Geometric Configuration  [PDF]
Tao Sun, Liang Lin, Qiaoyu Huang
Applied Mathematics (AM) , 2011, DOI: 10.4236/am.2011.27121
Abstract: The neuron growth will bring series variation to the neuron characteristics of geometric configuration. Especially the growth of dendrite and axon can obviously change the space characteristic and geometric characteristic of neuron. This article is to build the prediction model of neuron growth through knowing the statistics rules of neuron geometric characteristics, better imitate the neuron growth, and clearly analyze the growth influence of geometric configuration.
Comments on “Average Life Prediction Based on Incomplete Data”  [PDF]
Tachen Liang
Applied Mathematics (AM) , 2013, DOI: 10.4236/am.2013.412232

We comment on the correctness of the article “Average life prediction based on incomplete data” by [1] (Applied Mathematics, Vol. 2, pp. 93-105).

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