Malaria is the leading cause of morbidity and mortality in Kenya, with close to 70 percent (24 million) of the population at risk of infection. It affects people of all age groups: children under five years of age and...Malaria is the leading cause of morbidity and mortality in Kenya, with close to 70 percent (24 million) of the population at risk of infection. It affects people of all age groups: children under five years of age and pregnant women living in malaria endemic regions who are vulnerable. The main objective was to assess the utilization of the insecticide treated bed nets among the mothers attending MCH/FP in Webuye District Hospital, Bungoma County, Kenya. This research was based at the Webuye District Hospital, Bungoma County, Kenya from February to May, 2013. Sample size included 40 adult mothers attending MCH/FP aged 18 years and above during the study period. The design of the study was cross-sectional where sampling technique employed was non-probabilistic, purposive sampling. Data was collected by interviews using structured questionnaire which was administered by the researchers. SPSS version 16 was employed in Data analysis. The association between the overall knowledge about ITN use and malaria attack and level of education was tested and correlation between knowledge about malaria and ITNs utilization was calculated. Nearly all mothers attending MCH/FP had knowledge about ITNs nets and used it, with majority, 82.5% of the respondents used it for protection and 75% knew the importance of ITNs which were for malaria prevention. A majority of mothers attending MCH/FP were aware of ITNs and used it. Malaria morbidity was influenced by various factors including frequency of ITN use and most respondents interviewed had contracted malaria once before. The difference was found to be highly statistically significant between the overall knowledge about ITN use and malaria attack and level of education (χ2 = 58.7, p = 0.000). There was a significantly moderate positive correlation between total knowledge and ITN utilization (r = 0.449 & p = 0.000). The same was for the frequency of use but it was found to be in a weak magnitude, (r = 0.223 & p = 0.000). There was a strong positive correlation between knowledge about risk which is exposed to the case of non-utilization and the overall knowledge (r = 0.853 & p = 0.000). Based on the above results, it’s recommended that the Ministry of Health increase knowledge of effective malaria prevention and treatment methods in communities where misconceptions and use of unproven prevention and treatment methods are common.展开更多
The VRP is classified as an NP-hard problem. Hence exact optimization methods may be difficult to solve these problems in acceptable CPU times, when the problem involves real-world data sets that are very large. To ge...The VRP is classified as an NP-hard problem. Hence exact optimization methods may be difficult to solve these problems in acceptable CPU times, when the problem involves real-world data sets that are very large. To get solutions in determining routes which are realistic and very close to the actual solution, we use heuristics and metaheuristics which are of the combinatorial optimization type. A literature review of VRPTW, TDVRP, and a metaheuristic such as the genetic algorithm was conducted. In this paper, the implementation of the VRPTW and its extension, the time-dependent VRPTW (TDVRPTW) has been carried out using the model as well as metaheuristics such as the genetic algorithm (GA). The algorithms were implemented, using Matlab and HeuristicLab optimization software. A plugin was developed using Visual C# and DOT NET framework 4.5. Results were tested using Solomon’s 56 benchmark instances classified into groups such as C1, C2, R1, R2, RC1, RC2, with 100 customer nodes, 25 vehicles and each vehicle capacity of 200. The results were comparable to the earlier algorithms developed and in some cases the current algorithm yielded better results in terms of total distance travelled and the average number of vehicles used.展开更多
The aim of this work is mathematical education through the knowledge system and mathematical modeling. A net model of formation of mathematical knowledge as a deductive theory is suggested here. Within this model the ...The aim of this work is mathematical education through the knowledge system and mathematical modeling. A net model of formation of mathematical knowledge as a deductive theory is suggested here. Within this model the formation of deductive theory is represented as the development of a certain informational space, the elements of which are structured in the form of the orientated semantic net. This net is properly metrized and characterized by a certain system of coverings. It allows injecting net optimization parameters, regulating qualitative aspects of knowledge system under consideration. To regulate the creative processes of the formation and realization of mathematical know- edge, stochastic model of formation deductive theory is suggested here in the form of branching Markovian process, which is realized in the corresponding informational space as a semantic net. According to this stochastic model we can get correct foundation of criterion of optimization creative processes that leads to “great main points” strategy (GMP-strategy) in the process of realization of the effective control in the research work in the sphere of mathematics and its applications.展开更多
针对遥感图像建筑物的轮廓分割不完整、边界分割模糊和阴影干扰等导致的错误分割问题,提出一种基于VGG16的卷积块注意力深度可分离卷积U-Net网络(VGG16 Convolutional Block Attention and Deep Separable Convolution U-Net,VCDG-UNet...针对遥感图像建筑物的轮廓分割不完整、边界分割模糊和阴影干扰等导致的错误分割问题,提出一种基于VGG16的卷积块注意力深度可分离卷积U-Net网络(VGG16 Convolutional Block Attention and Deep Separable Convolution U-Net,VCDG-UNet)。为对建筑物特征进行提取,编码器部分模型以具有强大特征提取能力的VGG16作为骨干网络;解码器部分用深度可分离卷积代替普通卷积来减少参数量并融合不同尺度的特征;引入卷积块注意力模块(Convolutional Block Attention Module,CBAM)加入跳跃连接中,使其更有效地从不同尺度的图像中提取上下文信息并提高其对重要区域的关注度;为解决网络训练过程中的梯度消失问题,使用了高斯误差线性单元(Gaussian Error Linear Unit,GELU)。实验结果显示,改进后的网络在WHU和INRIA数据集上的平均交并比(mean Intersection over Union,mIoU)和F1-score分别达到了94.20%、96.83%和89.69%、94.51%,相较于基础模型高出了1.59%、0.76%和2.8%、1.59%。展开更多
文摘Malaria is the leading cause of morbidity and mortality in Kenya, with close to 70 percent (24 million) of the population at risk of infection. It affects people of all age groups: children under five years of age and pregnant women living in malaria endemic regions who are vulnerable. The main objective was to assess the utilization of the insecticide treated bed nets among the mothers attending MCH/FP in Webuye District Hospital, Bungoma County, Kenya. This research was based at the Webuye District Hospital, Bungoma County, Kenya from February to May, 2013. Sample size included 40 adult mothers attending MCH/FP aged 18 years and above during the study period. The design of the study was cross-sectional where sampling technique employed was non-probabilistic, purposive sampling. Data was collected by interviews using structured questionnaire which was administered by the researchers. SPSS version 16 was employed in Data analysis. The association between the overall knowledge about ITN use and malaria attack and level of education was tested and correlation between knowledge about malaria and ITNs utilization was calculated. Nearly all mothers attending MCH/FP had knowledge about ITNs nets and used it, with majority, 82.5% of the respondents used it for protection and 75% knew the importance of ITNs which were for malaria prevention. A majority of mothers attending MCH/FP were aware of ITNs and used it. Malaria morbidity was influenced by various factors including frequency of ITN use and most respondents interviewed had contracted malaria once before. The difference was found to be highly statistically significant between the overall knowledge about ITN use and malaria attack and level of education (χ2 = 58.7, p = 0.000). There was a significantly moderate positive correlation between total knowledge and ITN utilization (r = 0.449 & p = 0.000). The same was for the frequency of use but it was found to be in a weak magnitude, (r = 0.223 & p = 0.000). There was a strong positive correlation between knowledge about risk which is exposed to the case of non-utilization and the overall knowledge (r = 0.853 & p = 0.000). Based on the above results, it’s recommended that the Ministry of Health increase knowledge of effective malaria prevention and treatment methods in communities where misconceptions and use of unproven prevention and treatment methods are common.
文摘The VRP is classified as an NP-hard problem. Hence exact optimization methods may be difficult to solve these problems in acceptable CPU times, when the problem involves real-world data sets that are very large. To get solutions in determining routes which are realistic and very close to the actual solution, we use heuristics and metaheuristics which are of the combinatorial optimization type. A literature review of VRPTW, TDVRP, and a metaheuristic such as the genetic algorithm was conducted. In this paper, the implementation of the VRPTW and its extension, the time-dependent VRPTW (TDVRPTW) has been carried out using the model as well as metaheuristics such as the genetic algorithm (GA). The algorithms were implemented, using Matlab and HeuristicLab optimization software. A plugin was developed using Visual C# and DOT NET framework 4.5. Results were tested using Solomon’s 56 benchmark instances classified into groups such as C1, C2, R1, R2, RC1, RC2, with 100 customer nodes, 25 vehicles and each vehicle capacity of 200. The results were comparable to the earlier algorithms developed and in some cases the current algorithm yielded better results in terms of total distance travelled and the average number of vehicles used.
文摘The aim of this work is mathematical education through the knowledge system and mathematical modeling. A net model of formation of mathematical knowledge as a deductive theory is suggested here. Within this model the formation of deductive theory is represented as the development of a certain informational space, the elements of which are structured in the form of the orientated semantic net. This net is properly metrized and characterized by a certain system of coverings. It allows injecting net optimization parameters, regulating qualitative aspects of knowledge system under consideration. To regulate the creative processes of the formation and realization of mathematical know- edge, stochastic model of formation deductive theory is suggested here in the form of branching Markovian process, which is realized in the corresponding informational space as a semantic net. According to this stochastic model we can get correct foundation of criterion of optimization creative processes that leads to “great main points” strategy (GMP-strategy) in the process of realization of the effective control in the research work in the sphere of mathematics and its applications.
文摘针对遥感图像建筑物的轮廓分割不完整、边界分割模糊和阴影干扰等导致的错误分割问题,提出一种基于VGG16的卷积块注意力深度可分离卷积U-Net网络(VGG16 Convolutional Block Attention and Deep Separable Convolution U-Net,VCDG-UNet)。为对建筑物特征进行提取,编码器部分模型以具有强大特征提取能力的VGG16作为骨干网络;解码器部分用深度可分离卷积代替普通卷积来减少参数量并融合不同尺度的特征;引入卷积块注意力模块(Convolutional Block Attention Module,CBAM)加入跳跃连接中,使其更有效地从不同尺度的图像中提取上下文信息并提高其对重要区域的关注度;为解决网络训练过程中的梯度消失问题,使用了高斯误差线性单元(Gaussian Error Linear Unit,GELU)。实验结果显示,改进后的网络在WHU和INRIA数据集上的平均交并比(mean Intersection over Union,mIoU)和F1-score分别达到了94.20%、96.83%和89.69%、94.51%,相较于基础模型高出了1.59%、0.76%和2.8%、1.59%。
