Pengaruh Aida (Attention, Interest, Desire, Action) Terhadap Efektifitas Iklan Online (Survei Pada Pembeli Di Toko Online Adorable Project)

This research aims to describe the factors determining of models of AIDA (attention, interest, desire, action), to describe the influence of AIDA (Attention, Interest, Desire, Action) toward online advertising, and to describe the most dominant AIDA factor toward online advertising. The result of this research based on 145 buyers of online shop Adorable Project With factor and mulitiple linear regression analysis the result of this research is formed four new factor named interest, desire, action, attention. Based on multiple linear regression analyze Interest, Desire, Action are significant toward online advertising and factor attention is not significant toward online advertising in partial test and factor attention, interest, desire, action are significant influential in simultaneous test. Interest factor is the dominant factor in determine of online advertising

Does self-assessed health measure health?

Despite concerns about reporting biases and interpretation, self-assessed health (SAH) remains the measure of health most used by researchers, in part reflecting its ease of collection and in part the observed correlation between SAH and objective measures of health. Using a unique Australian data set, which consists of survey data linked to administrative individual medical records, we present empirical evidence demonstrating that SAH indeed predicts future health, as measured by hospitalizations, out-of-hospital medical services and prescription drugs. Our large sample size allows very disaggregate analysis and we find that SAH predicts more serious, chronic illnesses better than less serious illnesses. Finally, we compare the predictive power of SAH relative to administrative data and an extensive set of self-reported health measures; SAH does not add to the predictive power of future utilization when the administrative data is included and improves prediction only marginally when the extensive survey-based health measures are included. Clearly there is value in the more extensive survey and administrative health data as well as greater cost of collection

Dampak Pelatihan Konstruksi Bangunan Tahan Gempa Terhadap Perbaikan Kinerja Buruh Bangunan

This research aim to re-build labours capacity on concept and knowledge about housing throughconstruction workshop in endure building from earthquake. The result from this research found thatknowledge of participant had been increase to 41% (fourty one percents) through the workshop

Magnetic Table Interface and Magnetic Foods

This poster paper discuss the concept of magnetic table interface and magnetic foods. This interface introduces new human-food interactions such as modifying weight, levitation, movement, and dynamic textures for our daily used food and utensils using a strong magnetic field formed by an array of Bitter electromagnets. To make foods and cutleries interactive, we add edible magnetic material on the food such as iron and iron oxides, and make cutleries with magnetic materials. We expect that this system will alter our food consumption behaviours and make the whole experience much more interactive and enjoyable

An Extension and Further Validation of a Community-based Consumer Well-being Measure

Cataloged from PDF version of article.The goal of this study is to extend the research and further validation of Lee and colleagues' measure of community-based consumer well-being. The measure is based on the notion that consumers experience well-being to the extent that they are satisfied with local marketplace experiences related to (1) shopping for desired consumer goods and services in the local area, (2) preparing locally purchased consumer durables for personal use, (3) consuming locally purchased goods and services, (4) owning consumer durables purchased in the local area, (5) using repair and maintenance services in the local area, and (6) using selling, trading-in, and disposal services in the local area. Data were collected from ten localities in nine countries/states (California, Minnesota, Canada, Australia, Spain, Germany, Switzerland, Turkey, Egypt, and China) using the mall intercept method. The data provided support for the predictive/nomological validity of the measure by providing empirical support for the relationship between the consumer well-being construct and other well-being constructs such as life satisfaction

Effect of honey and ginger mixture on productive cough in pediatrics patients

Background: Cough is common problem in pediatric age. Most of the parents use over the counter drugs along with cough syrups. Most of the cough syrup causes drowsiness and sedation as an adverse effect. So considering this we use ginger and honey mixture for treatment of productive cough to see its effectiveness. In Ayurveda, it is used since ancient time and in Indian it is used for home remedy for treatment of cough.Methods: We selected patient attended pediatric outpatient department (OPD) complaining of productive cough. We selected 90 patients and divided in to three groups 30 patient in each group. Group I we gave antibiotics, antihistaminic with syrup ascoril (ambroxol 30 mg/5 ml and levosalbutamol 1 mg/5 ml and guaifenesin 50 mg/5 ml). Group II antibiotics, antihistaminic with honey and ginger mixture. In group III we gave antibiotic with antihistaminic along with both honey and ginger mixture with syrup ascoril. After this complete follow up to 10 days on mobile performed. We observed for occurrence of any deterioration of condition with occurrence adverse effect and how many days were required for improvement of patient condition.Results: We got very promising results were we saw improvement in symptom in 6 day with honey and ginger group as compared to cough syrup group were p value is significant and highly significant (<0.005 and 0.001 respectively) with minimal acceptable adverse effect.Conclusions: So from our study we can conclude the honey and ginger mixture is promising treatment of productive cough with less side effects

Machine Learning based prediction of Vanadium Redox Flow Battery temperature rise under different charge-discharge conditions

Accurate prediction of battery temperature rise is very essential for designing an efficient thermal management scheme. In this paper, machine learning (ML) based prediction of Vanadium Redox Flow Battery (VRFB) thermal behavior during charge-discharge operation has been demonstrated for the first time. Considering different currents with a specified electrolyte flow rate, the temperature of a kW scale VRFB system is studied through experiments. Three different ML algorithms; Linear Regression (LR), Support Vector Regression (SVR) and Extreme Gradient Boost (XGBoost) have been used for the prediction work. The training and validation of ML algorithms have been done by the practical dataset of a 1kW 6kWh VRFB storage under 40A, 45A, 50A and 60A charge-discharge currents and 10 L min-1 of flow rate. A comparative analysis among the ML algorithms is done in terms of performance metrics such as correlation coefficient (R2), mean absolute error (MAE) and root mean square error (RMSE). It is observed that XGBoost shows the highest accuracy in prediction of around 99%. The ML based prediction results obtained in this work can be very useful for controlling the VRFB temperature rise during operation and act as indicator for further development of an optimized thermal management system.Comment: 21 pages, 5 figure