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E-commerce has become very important in our daily lives. Many business transactions are made easier on this platform. Sellers and consumers are the two main parties that gain a lot of benefits from it. Although many sellers are attracted to set up their businesses on this online platform, it also causes challenges such as a highly competitive business environment and unpredictable sales. Thus, we propose a data analytics approach for short-term sales forecasts using limited information in the ecommerce marketplace. Product details are scraped from the e-commerce marketplace using a content scraping tool. Since the information in the e-commerce marketplace is limited and essential, scraped product details are pre-processed and constructed into meaningful data. These data are used in the computation of the forecasting methods. Three types of quantitative forecasting methods are computed and compared. These are simple moving average, dynamic linear regression and exponential smoothing. Three different evaluation metrics, namely mean absolute deviation, mean absolute percentage error and mean squared error, are used for the performance evaluation in order to determine the most suitable forecasting method. In our experiment, we found that the simple moving average has the best forecasting accuracy among other forecasting methods. Therefore, the application of the simple moving average forecasting method is suitable and can be used in the e-commerce marketplace for sales forecasting.

Garbage-man-in-the-middle (type 1) attack is an attack exploit the polynomial structure of LUC-type cryptosystems and depends on the possibility to get the faulty plaintext in the bin of the receiver. This paper reports an investigation for LUC-type cryptosystems under garbage-man-in-the middle (type 1) attack. Among all LUC-type cryptosystems, LUC, LUC3, and LUC4, 6 are selected to analyze their security. Results show that the attack fully success into the selected LUC-type cryptosystems under certain conditions.

2D surface flow models are useful to understand and predict the flow through breach, over a dyke or over the floodplains. This paper is aimed at the surface flows to study the behavior of flood waves. The open channel water flow in drains and rivers is considered in view of the fact that such flows are the source of flash flood. In order to predict and simulate the flood behavior, a mathematical model with the initial and boundary conditions is established using 2D Saint-Venant partial differential equations. Next, the corresponding model is discretized by using the explicit finite difference method and implemented on MATLAB. For the testing and implementation purpose a simple rectangular flow channel is considered. The output parameters like height or depth of water z (m), the fluid velocity u (m/s) and the volumetric flow rate Q (m3/sec) are simulated numerically and visualized for the different time steps. The initial simulation results are useful to understand and predict the flood behavior at different locations of flow channel at specific time steps and can be helpful in early flood warning systems. It is also suggested that the coupling of the subsurface flow with the surface flow may provide even better approximations for the flood circulation.