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Additive manufacturing (3D printing) is a hopeful technique that is used to produce complex geometry parts in a layer-by-layer method. Fused deposition modeling (FDM) is a popular 3D printing technology for producing components of thermoplastic polymers. In FDM process, the part quality is influenced strongly by the printing parameters. Until now, these parameters stil need to be investigated. Therefore, in this study, the influence of FDM 3D printing parameters on the tensile strength of product will be investigated. By experiment, three parameters, that is, layer height, solid layer top, and first-layer height, were studied. The investigation shows that the layer height is the only parameter impacted the tensile strength of the product.

The mechanical properties of thixoextrusion components can be improved by controllable processing parameters such as the solid fraction of alloy, holding time, punch velocity, heat treatment and die temperature. In this study, the effects of thixoforming parameters on the microstructures and mechanical properties of thixoextrusion ADC12 alloy Aptomat Contact are studied. ADC12 has excellent castability with high fluidity and low shrinkage rate, so it is widely used in industry, especially in automotive and motorcycle engine part casting. It is a near eutectic alloy with high strength and low ductility (1%). The optimization parameters mechanical properties were investigated by changing the punch velocity, specimen temperature and holding time. The results also indicated optimal value at punch velocity (15 mm/s), specimen temperature (560 °C) and holding time (5 min) which was changed microstructure from eutectic dendrite to globular grain, increasing the ductility (3.3%) of this alloy during the semi-solid forming process while the remaining mechanical properties lead to an increase in the quality of finished parts.

The thixoforming process is becoming more and more important in the field of metal-forming. In this process, the most difficult part is heating the sample while keeping the temperature uniform. The pressing speed is one of the main parameters that impacts strongly on product quality. In this paper, the die for studying the effect of pressing speed was designed and manufactured. The Deform 3D software was applied for observing the relationship between the pressing speed and the force history, stress, and temperature distribution. The results show that a pressing speed of v = 8 mm/s results in the smallest stress. The stress depends on many elements. For example, the pressing speed of v = 6 mm/s makes the heating process happen fast. The billet is cooled faster so the stress increases and even changes the structure unexpectedly. When the pressing speed is too high, the metal on the surface of the billet flows with high speed so it collides with the folding segments causing great resistance thus creating high stress.

We describe a model of entry timing assuming that a second mover can benefit from observing the experience of a first mover. We focus on how market attractiveness characteristics such as size and cost affect the time until first entry. The effects depend on whether the number of participants is exogenous or endogenous. In the former case, a more attractive market leads to earlier entry. In the latter case, it leads to later entry. Treating the number of firms as an integer, free entry leads to non-monotone, but testable, effects of market attractiveness on entry timing.

In the Automatic License Plate Recognition (ALPR) system, the License Plate Location (LPL) is the key step before the final recognition. This paper proposed an improved LPL algorithm for Vietnam vehicle license plates (LP). The proposed algorithm consists of three main modules: Pre-processing (convert RGB image to grayscale image, adjust grayscale image intensity, image binarization use Otsu method), LP candidates location (morphology opening to remove noises & dilation operation, measure properties of image regions to find candidates), LP exactly location (finding the LP angle & rotating LP, cut exactly LP region). We implemented test for 350 Vietnam vehicle images, which obtained from the actual system, the average rate of accuracy of our method is 98.64%, our results are more exactly presented methods.

We present an investigation into macroscopic and microscopic behaviors of wet granular soils using the discrete element method (DEM) and the X-ray Computed Tomography (XRCT) observations. The specimens are first prepared in very loose states, with frictional spherical grains in the presence of a small amount of an interstitial liquid. Experimental oedometric tests are carried out with small glass beads, while DEM simulations implement a model of spherical grains joined by menisci. Both in experiments and in simulations, loose configurations with solid fraction as low as 0.30 are prepared under low stress, and undergo a gradual collapse in compression, until the solid fraction of cohesionless bead packs (0.58 to 0.6) is obtained. In the XRCT tests, four 3D tomography images corresponding to different typical stages of the compression curve are used to characterize the microstructure.

The Automatic License Plate Recognition (ALPR) system has wide application and very important in the Intelligent Transportation System (ITS) such as the Electronic Toll Collection (ETC) system. The purpose of this paper is designing an Automatic License Plate Recognition (ALPR) system, which will be applied for one-stop and non-stop ETC in Vietnam. Our ALPR system consists of two major parts: the first part is hardware system and the second part is software system. In the first part, the price, types of equipments and technology will be considered for designing, which satisfied for Vietnam environment, Vietnam regulation in the road pricing rules and Vietnam standard of ETC. In the second part, we will combined image processing technology and artificial neural network to proposed a improved software system, our software include four modules: image capture, license plate location, characters segmentation and characters recognition. Our ALPR software will be tested by 700 Vietnam vehicle images, which obtained from actual system and complex background: lightening conditions (night & day), license angles, illumination, size and type, colors and reflected light. Our ALPR software is more effective than some of the existing methods earlier, the efficiency of computing time & accuracy is improved and very satisfied for all types of Vietnam LP and Vietnam environment.

The Automatic License Plate Recognition (ALPR) is very important in the Intelligent Transportation System (ITS). In this paper we proposed an improved ALPR algorithm for Vietnam license plates (LP), which consists of three main modules: license plate location (LPL), character segmentation, character recognition. In the location work, we have improved algorithm based on edge detection, image subtraction, mathematic morphology to locate LP region, which considered removing noise. In the segmentation work, we have improved algorithm to get the segments in the LP by the peak-to-valley method in order to segment in digit images getting the two bounds of the each digit according to the statistical parameter. In the recognition work, we have used a Multi Layer Perceptron (MLP) neural network and back-propagation (BP) algorithm to recognize characters & numbers of the Vietnam LP, we used two networks for characters & numbers training with noises, in which the computing time and accuracy is improved. Our approach is more effective than some of the existing methods earlier and satisfied for Vietnam LP. We have been implemented on 600 images taken from actual scenes, different background such as light conditions (night and day), angles, illumination, size and type, colors, reflected light, dynamic conditions. The efficiency of the proposed approach is improved and average rate of accuracy of the one-row LP is 96.93%, two-row LP is 95.82%, higher than most of previous works.

The use of internet services for time sensitive applications like voice and video, requires the forecasting quality of service. The TCP/IP differentiated services structure is given to achieve this target. However, network congestion control is limited and comes from the high priority. Some studies are still seeking a replacement techniques such as random early detection (RED) and its modification to manage congestion. In this paper we present neural network control research results to implement RED, called NRED. We found that with neural network we can perform better for discrimination acts to cancel the packets for gathering traffic flow, and also provide better quality services to all types different traffic while ensuring high utilization.