We have used the ShenguangⅡlaser in third harmonic(351 nm)to investigate the emission of L-shell radiation in the 3.3–4.4 ke V range generated using thin foils of Sn coated onto a parylene substrate with irradiation...We have used the ShenguangⅡlaser in third harmonic(351 nm)to investigate the emission of L-shell radiation in the 3.3–4.4 ke V range generated using thin foils of Sn coated onto a parylene substrate with irradiation of order 1015 W cm-2 and nanosecond pulse duration.In our experiment,we have concentrated on assessing the emission on the non-laser irradiated side as this allows an experimental geometry relevant to experiments on photo-ionised plasmas where a secondary target must be placed close to the source,to achieve x-ray fluxes appropriate to astrophysical objects.Overall L-shell conversion efficiencies are estimated to be of order 1%,with little dependence on Sn thickness between 400 and 800 nm.展开更多
Guidance is offered for understanding and using the Legendre transformation and its associated duality among functions and curves. The genesis of this paper was encounters with colleagues and students asking about the...Guidance is offered for understanding and using the Legendre transformation and its associated duality among functions and curves. The genesis of this paper was encounters with colleagues and students asking about the transformation. A main feature is simplicity of exposition, while keeping in mind the purpose or application for using the transformation.展开更多
A few post-bloom thinners are available for apple (Malus domestica Borkh.) and the prospects for additional thinners appear to be limited. Application of blossom thinners may present a risk of overthining in the areas...A few post-bloom thinners are available for apple (Malus domestica Borkh.) and the prospects for additional thinners appear to be limited. Application of blossom thinners may present a risk of overthining in the areas where weather is less predictable. Thus, we studied the impacts of various rates of 1-aminocyclopropane-1-carboxylic acid (ACC) in three strains of “Fuji” apple and different rates of ACC and one rate of Ethrel in “Buckeye Gala” apple, when fruitlet diameter was about 20 mm, on fruit set, yield and fruit quality attributes at harvest, and return bloom in southwest Idaho in the Intermountain West region, USA. In 2013, application of Ethrel at 300 mg·L<sup>-1</sup> did not affect fruit set, fruit weight, diameter (D), length(L), or L/D ratio 34 days after application, or yield, fruit weight, color, russet, and starch degradation pattern (SDP) at harvest, while application of ACC at 150 mg·L<sup>-1</sup> or higher reduced fruit set by 19% to 34% in “Buckeye Gala” apple. In this cultivar, application of ACC at 350 mg·L<sup>-1</sup> significantly increased fruit weight, diameter and length 34 days after application, and increased fruit weight, color, and SDP at harvest time. Application of ACC at all rates reduced total yield per tree in “Buckeye Gala”. Application of ACC at 300 mg·L<sup>-1</sup> significantly reduced fruit set but applications of 150 mg·L<sup>-1</sup> or 300 mg·L<sup>-1</sup> ACC did not affect yield or quality attributes of “Sun Fuji” apple in Sunny Slope area in 2013. Application of ACC reduced fruit set and slightly increased fruit size in “Top Export Fuji” in 2013. Application of ACC at 600 mg·L<sup>-1</sup> significantly reduced fruit set in “Aztec Fuji” apple in 2014. Application of ACC in a season never reduced bloom density (return bloom) of the next season. Overall, we conclude that ACC is an excellent tool as a late-season post-bloom fruit thinner and can be effective when applied fruitlet diameter is展开更多
Cancer has become a cause of concern in recent years. Cancer genomics is currently a key research direction in the fields of genetic biology and biomedicine. This paper analyzes 5 different types of cancer genes, such...Cancer has become a cause of concern in recent years. Cancer genomics is currently a key research direction in the fields of genetic biology and biomedicine. This paper analyzes 5 different types of cancer genes, such as breast, kidney, colon, lung and prostate through machine learning methods, with the goal of building a robust classification model to identify each type of cancer, which will allow us to identify each type of cancer early, thereby reducing mortality.展开更多
Traffic sign recognition is an important task in intelligent transportation systems, which can improve road safety and reduce accidents. Algorithms based on deep learning have achieved remarkable results in traffic si...Traffic sign recognition is an important task in intelligent transportation systems, which can improve road safety and reduce accidents. Algorithms based on deep learning have achieved remarkable results in traffic sign recognition in recent years. In this paper, we build traffic sign recognition algorithms based on ResNet and CNN models, respectively. We evaluate the proposed algorithm on public datasets and compare. We first use the dataset of traffic sign images from Kaggle. And then designed ResNet-based and CNN-based architectures that can effectively capture the complex features of traffic signs. Our experiments show that our ResNet-based model achieves a recognition accuracy of 99% on the test set, and our CNN-based model achieves a recognition accuracy of 98% on the test set. Our proposed approach has the potential to improve traffic safety and can be used in various intelligent transportation systems.展开更多
Breast cancer is a significant health concern, necessitating accurate prediction models for early detection and improved patient outcomes. This study presents a comparative analysis of three machine learning models, n...Breast cancer is a significant health concern, necessitating accurate prediction models for early detection and improved patient outcomes. This study presents a comparative analysis of three machine learning models, namely, Logistic Regression, Decision Tree, and Random Forest, for breast cancer prediction using the Wisconsin breast cancer diagnostic dataset. The dataset comprises features computed from fine needle aspirate images of breast masses, with 357 benign and 212 malignant cases. The research findings highlight that the Random Forest model, leveraging the top 5 predictors—“concave points_mean”, “area_mean”, “radius_mean”, “perimeter_mean”, and “concavity_mean”, achieves the highest predictive accuracy of approximately 95% and a cross-validation score of approximately 93% for the test dataset. These results demonstrate the potential of machine learning approaches in breast cancer prediction, underscoring their importance in aiding early detection and diagnosis.展开更多
With the development of automatic driving and fuzzy theory, people pay more and more attention to the application of fuzzy logic in engineering technology. The automatic parking module in the automatic driving system ...With the development of automatic driving and fuzzy theory, people pay more and more attention to the application of fuzzy logic in engineering technology. The automatic parking module in the automatic driving system has always been the focus of research. Automatic parking modules can greatly assist drivers in parking operations, greatly reduce parking difficulties and make people more convenient and fast parking. In this paper, an automatic parking system based on the fuzzy controller is proposed. The fuzzy controller of automatic parking system is constructed by using fuzzy theory, and the robustness of the whole system is examined by fuzzy logic. Firstly, the vehicle motion rules and trajectory changes are analyzed in detail, and the real parking lot model is simulated. Then, the input and output variables of the whole system are analyzed by fuzzy theory and the membership function is constructed. Based on the experience of human experts, the parking rules are tested and summarized, and a reasonable and practical rule base is established. Finally, MATLAB is used to code, build the visual interface of parking lot and vehicles, and draw the cyclic iterative function to detect the vehicle position and direction angle, so as to act as a sensor. The results show that using a fuzzy controller to construct an automatic parking system can effectively improve the parking level.展开更多
基金supported by the UK Science and Technology Facilities Council,National Natural Science Foundation of China(No.11573040)Science Challenge Project(No.TZ2016005)The Royal Society International Exchange(No.IE161039).
文摘We have used the ShenguangⅡlaser in third harmonic(351 nm)to investigate the emission of L-shell radiation in the 3.3–4.4 ke V range generated using thin foils of Sn coated onto a parylene substrate with irradiation of order 1015 W cm-2 and nanosecond pulse duration.In our experiment,we have concentrated on assessing the emission on the non-laser irradiated side as this allows an experimental geometry relevant to experiments on photo-ionised plasmas where a secondary target must be placed close to the source,to achieve x-ray fluxes appropriate to astrophysical objects.Overall L-shell conversion efficiencies are estimated to be of order 1%,with little dependence on Sn thickness between 400 and 800 nm.
文摘Guidance is offered for understanding and using the Legendre transformation and its associated duality among functions and curves. The genesis of this paper was encounters with colleagues and students asking about the transformation. A main feature is simplicity of exposition, while keeping in mind the purpose or application for using the transformation.
文摘A few post-bloom thinners are available for apple (Malus domestica Borkh.) and the prospects for additional thinners appear to be limited. Application of blossom thinners may present a risk of overthining in the areas where weather is less predictable. Thus, we studied the impacts of various rates of 1-aminocyclopropane-1-carboxylic acid (ACC) in three strains of “Fuji” apple and different rates of ACC and one rate of Ethrel in “Buckeye Gala” apple, when fruitlet diameter was about 20 mm, on fruit set, yield and fruit quality attributes at harvest, and return bloom in southwest Idaho in the Intermountain West region, USA. In 2013, application of Ethrel at 300 mg·L<sup>-1</sup> did not affect fruit set, fruit weight, diameter (D), length(L), or L/D ratio 34 days after application, or yield, fruit weight, color, russet, and starch degradation pattern (SDP) at harvest, while application of ACC at 150 mg·L<sup>-1</sup> or higher reduced fruit set by 19% to 34% in “Buckeye Gala” apple. In this cultivar, application of ACC at 350 mg·L<sup>-1</sup> significantly increased fruit weight, diameter and length 34 days after application, and increased fruit weight, color, and SDP at harvest time. Application of ACC at all rates reduced total yield per tree in “Buckeye Gala”. Application of ACC at 300 mg·L<sup>-1</sup> significantly reduced fruit set but applications of 150 mg·L<sup>-1</sup> or 300 mg·L<sup>-1</sup> ACC did not affect yield or quality attributes of “Sun Fuji” apple in Sunny Slope area in 2013. Application of ACC reduced fruit set and slightly increased fruit size in “Top Export Fuji” in 2013. Application of ACC at 600 mg·L<sup>-1</sup> significantly reduced fruit set in “Aztec Fuji” apple in 2014. Application of ACC in a season never reduced bloom density (return bloom) of the next season. Overall, we conclude that ACC is an excellent tool as a late-season post-bloom fruit thinner and can be effective when applied fruitlet diameter is
文摘Cancer has become a cause of concern in recent years. Cancer genomics is currently a key research direction in the fields of genetic biology and biomedicine. This paper analyzes 5 different types of cancer genes, such as breast, kidney, colon, lung and prostate through machine learning methods, with the goal of building a robust classification model to identify each type of cancer, which will allow us to identify each type of cancer early, thereby reducing mortality.
文摘Traffic sign recognition is an important task in intelligent transportation systems, which can improve road safety and reduce accidents. Algorithms based on deep learning have achieved remarkable results in traffic sign recognition in recent years. In this paper, we build traffic sign recognition algorithms based on ResNet and CNN models, respectively. We evaluate the proposed algorithm on public datasets and compare. We first use the dataset of traffic sign images from Kaggle. And then designed ResNet-based and CNN-based architectures that can effectively capture the complex features of traffic signs. Our experiments show that our ResNet-based model achieves a recognition accuracy of 99% on the test set, and our CNN-based model achieves a recognition accuracy of 98% on the test set. Our proposed approach has the potential to improve traffic safety and can be used in various intelligent transportation systems.
文摘Breast cancer is a significant health concern, necessitating accurate prediction models for early detection and improved patient outcomes. This study presents a comparative analysis of three machine learning models, namely, Logistic Regression, Decision Tree, and Random Forest, for breast cancer prediction using the Wisconsin breast cancer diagnostic dataset. The dataset comprises features computed from fine needle aspirate images of breast masses, with 357 benign and 212 malignant cases. The research findings highlight that the Random Forest model, leveraging the top 5 predictors—“concave points_mean”, “area_mean”, “radius_mean”, “perimeter_mean”, and “concavity_mean”, achieves the highest predictive accuracy of approximately 95% and a cross-validation score of approximately 93% for the test dataset. These results demonstrate the potential of machine learning approaches in breast cancer prediction, underscoring their importance in aiding early detection and diagnosis.
文摘With the development of automatic driving and fuzzy theory, people pay more and more attention to the application of fuzzy logic in engineering technology. The automatic parking module in the automatic driving system has always been the focus of research. Automatic parking modules can greatly assist drivers in parking operations, greatly reduce parking difficulties and make people more convenient and fast parking. In this paper, an automatic parking system based on the fuzzy controller is proposed. The fuzzy controller of automatic parking system is constructed by using fuzzy theory, and the robustness of the whole system is examined by fuzzy logic. Firstly, the vehicle motion rules and trajectory changes are analyzed in detail, and the real parking lot model is simulated. Then, the input and output variables of the whole system are analyzed by fuzzy theory and the membership function is constructed. Based on the experience of human experts, the parking rules are tested and summarized, and a reasonable and practical rule base is established. Finally, MATLAB is used to code, build the visual interface of parking lot and vehicles, and draw the cyclic iterative function to detect the vehicle position and direction angle, so as to act as a sensor. The results show that using a fuzzy controller to construct an automatic parking system can effectively improve the parking level.
