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Investigation of radiation attenuation properties of Al-Cu matrix composites reinforced by different amount of B4 C particles
No full textİnme tanısı ile hastaneye yatırılan hastalara bakım verenlerin depresyon durumu ve yaşam kalitesi algıları
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Hematopoietik Kök Hücre Nakli Olmuş Hastalarda JC Virüs Pozitifliğinin Gerçek-Zamanlı Polimeraz Zincir Reaksiyonu ile Araştırılması
No full textDeep Learning Based Prediction Model for the Next Purchase
No full textTime series represent the consecutive measurements taken at equally
spaced time intervals. Time series prediction uses the information in a
time series to predict future values. The future value prediction is
important for many business and administrative decision makers
especially in e-commerce. To promote business, sales prediction and
sensing of future consumer behavior can help business decision makers in
marketing campaigns, budget and resource planning. In this study, deep
learning based a new prediction model has been developed for the time of
next purchase in e-commerce. The proposed model has been extensively
tested and compared with RF, ARIMA, CNN and MLP using a retail market
dataset. The experimental results show that the developed model has been
more successful than RF, ARIMA, CNN and MLP to predict the time of the
next purchase
Effect of serum uric acid (ua) level and MASCC risk score on febrile neutropenia mortality
No full textOutcomes after minimally-invasive versus open pancreatoduodenectomy: A pan-european propensity score matched study
No full textShape memory effect of polymeric composite materials filled with NiMnSbB shape memory alloy for textile materials
No full textThe aim of the study was to obtain a smart textile material with shape
memory alloys. NiMn-based shape memory alloy was produced by arc melting
system for this purpose. Phase transition temperatures of the fabricated
alloy were determined by using differential scanning calorimeter (DSC).
The crystallographic structure of the fabricated alloy was characterized
by x-ray diffractometer (XRD). The fabricated shape memory alloy was
converted to the particle form and filled into polymer matrix to obtain
shape memory effect of this polymeric composite material. Polymeric
composites (PCs) were produced in film form and shape training of PCs
were studied under different conditions. The shape memory behavior of
samples was investigated into the water for fast response during
applying heat. Damping capacity of composites was measured by using
dynamic mechanical analyzer (DMA) according to temperature rising. The
shape recovery was observed under certain stimuli on the SMA filled
polymeric composites