In order to improve the feasibility and accuracy of the roadbed settlement prediction model, the factor analysis method is combined with the BP neural network method, and an improved BP neural network roadbed settlement prediction model is proposed. Select example data to test the improved BP neural network roadbed settlement prediction model. The test results: The relative average error of the 10 sets of training samples’ predicted and actual roadbed settlements was 4.287%, and the roads of five predicted samples The relative error of subgrade settlement is 1.79%, 1.93%, 6.62%, 7.19%, 4.05%, all less than 10%, which proves that the improved BP neural network prediction model has good prediction accuracy.
In order to ensure the safe navigation of ships and reduce the occurrence of marine accidents, through the analysis of ship historical navigation safety accident data and related accident literature research, taking into account various aspects such as marine meteorology, cargo loading, ship status and crew quality. Construct a ship navigation safety evaluation body. The BP neural network algorithm is used to design the ship navigation safety risk network structure. The sea damage data is used as the network input sample to train the BP neural network and data fitting. At the same time, the genetic algorithm is introduced to find the individual corresponding to the optimal fitness, and the weight and threshold of the network are further optimized. The purpose is to improve the accuracy of data fitting. The optimized BP neural network evaluation results show that there are many indicators affecting the safety of the ship’s navigation, and the relationship between the indicators is complicated. The optimized BP neural network utilizes the characteristics of online adaptive learning, which eliminates the construction of complex relationships among various indicators within the structure, and solves the difficult problems in ship risk assessment to a certain extent.
Application of Reverse Car-seeking in Large Underground Parking Lot Based on A Star Algorithm: A Real Case
In order to solve the problems of low utilization rate of large parking lots and low efficiency of parking turnover, it is proposed to use A-star algorithm to plan the shortest path for finding a car, and run it in Android system to realize reverse car-searching. By analyzing the current situation of large underground parking lot barriers, A-star algorithm converts the starting point to the destination route into the corresponding parking space to the destination parking space path, calculates the optimal path and provides real-time path car navigation for the vehicle owner. According to the path searched by the A-star algorithm in the Android system, the time spent by the user to blindly search for the vehicle is largely saved, and the parking space utilization rate and the parking turnover rate are effectively improved. Therefore, the research has certain application value in the large parking lots.
Nexus between Theory and Practice of Continuous Assessment in Higher Education: Dawa University in Focus
The final goal of continuous assessment (CA) is to improve the quality of teaching and learning. This study examined the linkage between theoretical assumptions and the real practices of continuous assessment for quality teaching and learning in higher education institutions of Ethiopia, Dire Dawa University in focus. The study employed survey research design. The 73 educators and 289 learners were participated in the study. The study used 5-points Likert scale type data collection instrument. The data were analyzed via SPSS version 20. The data analysis technique employed was a one-sample t-test. The Cronbach’s alpha coefficient was used to test the reliability of instruments and thus, the questionnaires had acceptable alpha coefficients. This study revealed that the instructors and students have acknowledged the opportunities of CA to improve the quality of teaching and learning in HEIs. Finally, if CA is to fit for purpose, the practice of continuous assessment for marking students’ learning performance and for facilitating their further learning should be balanced based on theoretical assumptions. Besides, the need to design competency-based assessment rubric was recommended.
This paper studies the problem of site selection and tour route, establishes multi-objective decision model and optimizes the line model, uses the Floyd algorithm and uses MATLAB and lingo to program to provide the optimal scheme of site selection and tour route respectively. A single-target optimization model was established, a minimum value function was established for the total distance after weighting, the shortest path length of any two communities was calculated using the Floyd algorithm, and the site of the water and electricity payment was obtained to facilitate residents to pay the utility bill. By establishing the constraint optimization line model, the shortest path of any two residential areas is obtained by The Floyd algorithm, establish the shortest path spanning tree whose root is residential area no.6, and the regions are divided, then optimal tour is obtained.
In vitro EVALUATION OF ATOVAQUONE ON THE REPLICATION OF TOXOPLASMA GONDII TACHYZOITES STRAINS RH AND ME49
Introduction: Since 1990 the standard treatment for toxoplasmosis has remained the same. The therapy is based on a synergistic combination of pyrimethamine and sulfadiazine, drugs that promote synthesis blockade and decrease of tachyzoite folic acid levels. This therapy acts only on the tachyzoite forms of the parasite, not affecting bradyzoites present in tissue cysts that persist in the individual during the chronic phase and not preventing possible disease reagudization even after treatment. Given the high seroprevalence of toxoplasmosis in the general population and the serious complications that this infection may bring to the patient, a safe and effective treatment against all morphological forms is necessary. The repositioning of drugs main objective is to use substances already marketed to treat other diseases. Thus, Atovaquone, which is an antimalarial of the naphthoquinone group recently accepted by the FDA and isn’t yet part of the routine treatment protocols employed for toxoplasmosis, should be studied, as recent studies show its activity against tachyzoites and also against bradyzoites, representing a huge advantage over the drugs currently used. It also does not interfere with folic acid metabolism, proving to be a promising drug in the treatment of pregnant women. Objective: The present study aims to evaluate the effects of atovaquone on T. gondii strains RH and ME49 (type I and type II, respectively) in vitro. Methodology: In quintuplicate, murine RAW 264.7 macrophages were used in six-well culture plates with 3mL of supplemented RPMI medium, where 200.000 cells were seeded and incubated at 37°C, 5% de CO2 for 24 hours. After this period, the culture was infected with 1×106 tachyzoites/well of each strain analyzed and simultaneously treated with 100 nM Atovaquone. The parasites were analyzed by optical microscopy and quantified in a Neubauer chamber at 24h, 48h, 72h and 7 days. Results: For the RH strain, the…
In order to predict the duration of traffic congestion, this paper established a traffic congestion evaluation model based on cumulative ratio Logistic regression and a traffic congestion time prediction model based on BP neural network. Combining Pearson test, numerical combination, standard deviation method and other methods to solve the problem. Based on the measured data of Jinshui Road in Zhengzhou, the average error is 0.019m/ s and the prediction error rate is 0.15%, both within a reasonable range. The model can improve the accuracy of congestion time prediction and provide some help to real life.
Study on the generalized model of the lateral frictional resistance distribution under the ultimate state of the bored piles based on stratum structure
Based on the results of the ultimate load distribution of the part of the bored piles in the vertical static load field test of single pile, combined with the analysis of the relevant piles and soil data, found that the lateral friction resistance distribution of the bored pile in the ultimate load state was mainly related to structure of the soil layer on the pile side. Based on this, the side resistance distribution mode of the pile under the ultimate load conditions is generalized into a trapezoid, wing-shaped, micro-arc, and “R” shaped. The lateral friction resistance of the pile is positively correlated with the hardness of the soil, and the depth, thickness can influence the pattern of distribution of lateral friction resistance.
With the rapid development of the Internet, personalized recommendation has become an indispensable part of e-commerce system. How to solve the miscellaneous information in e-commerce system through personalized recommendation has become a research hotspot. This paper analyses the development background and significance of personalized recommendation, compares and analyses the relevant algorithms of personalized recommendation through the research of e-commerce system and personalized recommendation, and deeply studies the application of personalized recommendation technology in e-commerce system. The research of personalized recommendation system will contribute to the further development of e-commerce system and make Internet life closer to reality.
In order to solve the problem of excessive Mn(II) content in water in some areas of China, TiO2 nanotubes and TiO2 powder are used to remove Mn(II). The experimental results show that both TiO2 nanotubes and TiO2 powder have certain manganese removal effect, and the effect of powder is better. When the pH was 5.6 and the 20W UV lamp was irradiated for 40 min, the removal rate of the powder was 64.3 %, and the removal rate of the nanotubes anodized for 1h was 35.3 %, and the removal rate of the nanotubes anodized for 30 min was 23.9 %. When the pH is adjusted to 7-8, the removal rate of the nanotubes is significantly improved. When the pH was 8, 20W UV lamp was irradiated for 40 min, the removal rate of nanotubes anodized for 1h was 60.4%.