Structural development defects essentially refer to code structure that violates object-oriented design principles. They make program maintenance challenging and deteriorate software quality over time. Various detecti...Structural development defects essentially refer to code structure that violates object-oriented design principles. They make program maintenance challenging and deteriorate software quality over time. Various detection approaches, ranging from traditional heuristic algorithms to machine learning methods, are used to identify these defects. Ensemble learning methods have strengthened the detection of these defects. However, existing approaches do not simultaneously exploit the capabilities of extracting relevant features from pre-trained models and the performance of neural networks for the classification task. Therefore, our goal has been to design a model that combines a pre-trained model to extract relevant features from code excerpts through transfer learning and a bagging method with a base estimator, a dense neural network, for defect classification. To achieve this, we composed multiple samples of the same size with replacements from the imbalanced dataset MLCQ1. For all the samples, we used the CodeT5-small variant to extract features and trained a bagging method with the neural network Roberta Classification Head to classify defects based on these features. We then compared this model to RandomForest, one of the ensemble methods that yields good results. Our experiments showed that the number of base estimators to use for bagging depends on the defect to be detected. Next, we observed that it was not necessary to use a data balancing technique with our model when the imbalance rate was 23%. Finally, for blob detection, RandomForest had a median MCC value of 0.36 compared to 0.12 for our method. However, our method was predominant in Long Method detection with a median MCC value of 0.53 compared to 0.42 for RandomForest. These results suggest that the performance of ensemble methods in detecting structural development defects is dependent on specific defects.展开更多
XRF and EDX analyses were carried out on 18 batches of representative raw samples to determine the distribution of major chemical elements in the petroleum source rocks of Donga and Yogou formations of Termit sediment...XRF and EDX analyses were carried out on 18 batches of representative raw samples to determine the distribution of major chemical elements in the petroleum source rocks of Donga and Yogou formations of Termit sedimentary basin. The chemical composition of these formations is dominated by silicon (Si), aluminum (Al) and iron (Fe). This is consistent with the oxide composition, which is also dominated by silicon oxide (SiO2), aluminum oxide (Al<sub>2</sub>O<sub>3</sub>) and iron monoxide (FeO). No less important chemical elements are calcium (Ca), potassium (K), sulfur (S), titanium (Ti), magnesium (Mg), manganese (Mn) and barium (Ba), as well as some of their oxides. All these major chemical elements are carried by silicate detrital minerals associated with pyrite and goethite and/or clay minerals such as kaolinite and interstratified illite, smectite and chlorite. This trend is illustrated by the values of the Si/Al and SiO<sub>2</sub>/Al<sub>2</sub>O<sub>3</sub> ratios.展开更多
This paper assesses the vehicle dynamics of a new cargo bike concept developed for euro pallet sized cargo. The cargo bike developed is for last-mile delivery. Different aspects of manoeuvrability and stability are ex...This paper assesses the vehicle dynamics of a new cargo bike concept developed for euro pallet sized cargo. The cargo bike developed is for last-mile delivery. Different aspects of manoeuvrability and stability are examined using a series of manoeuvres based on tests from the automotive industry combined with bicycle industry regulations. These manoeuvres objectively evaluate and determine the handling capabilities of the cargo bike concept. Those tests can be compared using the results of the benchmark vehicles. The results conclude the new cargo bike has proper vehicle dynamics above the majority of benchmark vehicles but there is still room for improvement.展开更多
Deep learning (DL) has experienced an exponential development in recent years, with major impact in many medical fields, especially in the field of medical image and, respectively, as a specific task, in the segmentat...Deep learning (DL) has experienced an exponential development in recent years, with major impact in many medical fields, especially in the field of medical image and, respectively, as a specific task, in the segmentation of the medical image. We aim to create a computer assisted diagnostic method, optimized by the use of deep learning (DL) and validated by a randomized controlled clinical trial, is a highly automated tool for diagnosing and staging precancerous and cervical cancer and thyroid cancers. We aim to design a high-performance deep learning model, combined from convolutional neural network (U-Net)-based architectures, for segmentation of the medical image that is independent of the type of organs/tissues, dimensions or type of image (2D/3D) and to validate the DL model in a randomized, controlled clinical trial. We used as a methodology primarily the analysis of U-Net-based architectures to identify the key elements that we considered important in the design and optimization of the combined DL model, from the U-Net-based architectures, imagined by us. Secondly, we will validate the performance of the DL model through a randomized controlled clinical trial. The DL model designed by us will be a highly automated tool for diagnosing and staging precancers and cervical cancer and thyroid cancers. The combined model we designed takes into account the key features of each of the architectures Overcomplete Convolutional Network Kite-Net (Kite-Net), Attention gate mechanism is an improvement added on convolutional network architecture for fast and precise segmentation of images (Attention U-Net), Harmony Densely Connected Network-Medical image Segmentation (HarDNet-MSEG). In this regard, we will create a comprehensive computer assisted diagnostic methodology validated by a randomized controlled clinical trial. The model will be a highly automated tool for diagnosing and staging precancers and cervical cancer and thyroid cancers. This would help drastically minimize the time and effort that specialists put into analyzing medical images, help to achieve a better therapeutic plan, and can provide a “second opinion” of computer assisted diagnosis.展开更多
Many datasets in E-commerce have rich information about items and users who purchase or rate them. This information can enable advanced machine learning algorithms to extract and assign user sentiments to various aspe...Many datasets in E-commerce have rich information about items and users who purchase or rate them. This information can enable advanced machine learning algorithms to extract and assign user sentiments to various aspects of the items thus leading to more sophisticated and justifiable recommendations. However, most Collaborative Filtering (CF) techniques rely mainly on the overall preferences of users toward items only. And there is lack of conceptual and computational framework that enables an understandable aspect-based AI approach to recommending items to users. In this paper, we propose concepts and computational tools that can sharpen the logic of recommendations and that rely on users’ sentiments along various aspects of items. These concepts include: The sentiment of a user towards a specific aspect of a specific item, the emphasis that a given user places on a specific aspect in general, the popularity and controversy of an aspect among groups of users, clusters of users emphasizing a given aspect, clusters of items that are popular among a group of users and so forth. The framework introduced in this study is developed in terms of user emphasis, aspect popularity, aspect controversy, and users and items similarity. Towards this end, we introduce the Aspect-Based Collaborative Filtering Toolbox (ABCFT), where the tools are all developed based on the three-index sentiment tensor with the indices being the user, item, and aspect. The toolbox computes solutions to the questions alluded to above. We illustrate the methodology using a hotel review dataset having around 6000 users, 400 hotels and 6 aspects.展开更多
Recent experimental progress in JT-60U advanced tokamak research is presented： sustainment of the normalized beta （βN）- 3 in a normal magnetic shear plasma, the bootstrap current fraction （fBs） - 45% in a weak s...Recent experimental progress in JT-60U advanced tokamak research is presented： sustainment of the normalized beta （βN）- 3 in a normal magnetic shear plasma, the bootstrap current fraction （fBs） - 45% in a weak shear plasma and - 75% in a reversed magnetic shear plasma in a nearly fully non-inductive current drive condition for longer than the current relaxation time. Achievement of high-density, high-radiation fraction together with high-confinement in advanced plasmas is demonstrated. Achievements and findings in long pulse operations after system modification are presented as well. A 65 s discharge of Ip = 0.7 MA was successfully obtained. As a result, high-βN of 2.3 was successfully sustained for a very long period of 22.3 s. In addition, a 30 s standard ELMy H-mode plasma of Ip up to 1.4 MA was also obtained. Effectiveness of divertor pumping to control particle recycling and the electron density under the saturated wall retention was demonstrated. These achievements and issues in development are discussed.展开更多
Probiotification of plant milk can improve its sensory and health-promoting properties. As traditional fermented foods where lactic acid bacteria (LAB) are present have been associated with beneficial effects on human...Probiotification of plant milk can improve its sensory and health-promoting properties. As traditional fermented foods where lactic acid bacteria (LAB) are present have been associated with beneficial effects on human health, the beneficial effects of two LAB recently isolated from two current Ivorian staple foods (a pepper and a traditional beer) were screened. These two strains LAC 1 (Lactobacillus plantarum) and LAC 2 (Pediococcus acidilactici) which presented probiotic, exopolysaccharides, inflammatory and anti-oxidant activities, were used to ferment a composite plant milk of tiger-nut and cashew (80/20) compared to two starters of a commercial yogourt. The obtained plant milks SCT 2 and SCT 3 with a significant increase in their antioxidant and/or anti-inflammatory activities and lactic bacteria contents were more preferred by consumers than SCT 1 obtained by fermentation of the commercial yogourt starters. The mixing of LAC 1 and LAC 2 was not beneficial. SCT 2 (with an anti-inflammatory activity of 31.38% and an anti-oxidant activity of 17.30%) and SCT 3 (with an anti-oxidant activity of 22.28) could be further tested in animal models to verify their nutrition-health claims.展开更多
<div style="text-align:justify;"> <span style="line-height:1.5;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">Pathologies transm...<div style="text-align:justify;"> <span style="line-height:1.5;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">Pathologies transmissible by hand such as gastrointestinal pathologies constitute a real public health problem, especially in sub-Saharan Africa where hygienic conditions are precarious. This study took place at Félix Houphou</span><span style="white-space:nowrap;font-family:Verdana;">ë</span><span style="font-family:Verdana;"></span></span><span style="font-family:Verdana;">t-Boigny</span></span><span "="" style="line-height:1.5;"><span style="font-family:Verdana;"> University from April to August 2018. The samples were taken from toilet surfaces such as doorknobs, tap heads, flush push buttons and seats WC. A total of three hundred and sixty-eight (368) samples were obtained, including 170 from the staff toilets and 198 from the student toilets. The results revealed the presence of total coliforms, </span><i><span style="font-family:Verdana;">Escherichia</span></i><span style="font-family:Verdana;"> spp and </span><i><span style="font-family:Verdana;">Salmonella</span></i><span style="font-family:Verdana;"><span style="font-family:Verdana;"> spp. The surfaces of student toilets were the most contaminated surfaces. The presence of entero-bacteria on the contact surfaces of the toilets of the Félix Houphou</span><span style="white-space:nowrap;font-family:Verdana;">ë</span><span style="font-family:Verdana;"></span></span><span style="font-family:Verdana;">t-Boigny university represents a health risk for the university population.</span></span> </div>展开更多
The decrease of fertility soils, the rarity of quality potting soil used to fill nursery bags, the high cost of chemical fertilisers and the problems associated with their use are leading planters and rubber nurseryme...The decrease of fertility soils, the rarity of quality potting soil used to fill nursery bags, the high cost of chemical fertilisers and the problems associated with their use are leading planters and rubber nurserymen in developing and/or expanding areas to look for alternative and sustainable fertilization. In this perspective, a trial was carried out at Research Station of CNRA-Bimbresso and in a farmer’s environment in order to evaluate the agronomic quality of compost made from chicken droppings and dry <em>Panicum maximum</em> straw to improve the growth of rubber plants in bagged nurseries. Mixtures based on potting soil and/or compost in different proportions were prepared. The follow-up of the trial focused on determination of the physico-chemical characteristics of the soils, measurement of the parameters of vegetative growth and the grafting success rate evaluation of rubber plants in nursery. The results obtained show that compost-based crop substrates increase soil organic matter, nitrogen, exchangeable bases, etc., in proportion to the doses applied. For the pH, the application of compost resulted in a reduction in soil acidity of about 1.3 unit compared to the initial values at the two study sites. The vegetative behaviour of the rubber plants also shows that qualitative (height and collar diameter) and quantitative (grafting success rate) improvements were recorded in the plants raised in compost-based substrates. The production of rubber plants in bagged nurseries was optimal with compost doses of 27 t<span style="white-space:nowrap;">⋅</span>ha<sup><span style="white-space:nowrap;">−</span>1</sup> (at Bimbresso, in the southeast) and 27 t<span style="white-space:nowrap;">⋅</span>ha<sup><span style="white-space:nowrap;">−</span>1</sup> combined with fractionated application of urea (at Kimoukro, in the centre), which under the conditions of the present study may be the recommended doses on rubber plants in bagged nurseries at C<span style="white-space:nowrap;">ô</span>te d’Ivoire.展开更多
文摘Structural development defects essentially refer to code structure that violates object-oriented design principles. They make program maintenance challenging and deteriorate software quality over time. Various detection approaches, ranging from traditional heuristic algorithms to machine learning methods, are used to identify these defects. Ensemble learning methods have strengthened the detection of these defects. However, existing approaches do not simultaneously exploit the capabilities of extracting relevant features from pre-trained models and the performance of neural networks for the classification task. Therefore, our goal has been to design a model that combines a pre-trained model to extract relevant features from code excerpts through transfer learning and a bagging method with a base estimator, a dense neural network, for defect classification. To achieve this, we composed multiple samples of the same size with replacements from the imbalanced dataset MLCQ1. For all the samples, we used the CodeT5-small variant to extract features and trained a bagging method with the neural network Roberta Classification Head to classify defects based on these features. We then compared this model to RandomForest, one of the ensemble methods that yields good results. Our experiments showed that the number of base estimators to use for bagging depends on the defect to be detected. Next, we observed that it was not necessary to use a data balancing technique with our model when the imbalance rate was 23%. Finally, for blob detection, RandomForest had a median MCC value of 0.36 compared to 0.12 for our method. However, our method was predominant in Long Method detection with a median MCC value of 0.53 compared to 0.42 for RandomForest. These results suggest that the performance of ensemble methods in detecting structural development defects is dependent on specific defects.
文摘XRF and EDX analyses were carried out on 18 batches of representative raw samples to determine the distribution of major chemical elements in the petroleum source rocks of Donga and Yogou formations of Termit sedimentary basin. The chemical composition of these formations is dominated by silicon (Si), aluminum (Al) and iron (Fe). This is consistent with the oxide composition, which is also dominated by silicon oxide (SiO2), aluminum oxide (Al<sub>2</sub>O<sub>3</sub>) and iron monoxide (FeO). No less important chemical elements are calcium (Ca), potassium (K), sulfur (S), titanium (Ti), magnesium (Mg), manganese (Mn) and barium (Ba), as well as some of their oxides. All these major chemical elements are carried by silicate detrital minerals associated with pyrite and goethite and/or clay minerals such as kaolinite and interstratified illite, smectite and chlorite. This trend is illustrated by the values of the Si/Al and SiO<sub>2</sub>/Al<sub>2</sub>O<sub>3</sub> ratios.
文摘This paper assesses the vehicle dynamics of a new cargo bike concept developed for euro pallet sized cargo. The cargo bike developed is for last-mile delivery. Different aspects of manoeuvrability and stability are examined using a series of manoeuvres based on tests from the automotive industry combined with bicycle industry regulations. These manoeuvres objectively evaluate and determine the handling capabilities of the cargo bike concept. Those tests can be compared using the results of the benchmark vehicles. The results conclude the new cargo bike has proper vehicle dynamics above the majority of benchmark vehicles but there is still room for improvement.
文摘Deep learning (DL) has experienced an exponential development in recent years, with major impact in many medical fields, especially in the field of medical image and, respectively, as a specific task, in the segmentation of the medical image. We aim to create a computer assisted diagnostic method, optimized by the use of deep learning (DL) and validated by a randomized controlled clinical trial, is a highly automated tool for diagnosing and staging precancerous and cervical cancer and thyroid cancers. We aim to design a high-performance deep learning model, combined from convolutional neural network (U-Net)-based architectures, for segmentation of the medical image that is independent of the type of organs/tissues, dimensions or type of image (2D/3D) and to validate the DL model in a randomized, controlled clinical trial. We used as a methodology primarily the analysis of U-Net-based architectures to identify the key elements that we considered important in the design and optimization of the combined DL model, from the U-Net-based architectures, imagined by us. Secondly, we will validate the performance of the DL model through a randomized controlled clinical trial. The DL model designed by us will be a highly automated tool for diagnosing and staging precancers and cervical cancer and thyroid cancers. The combined model we designed takes into account the key features of each of the architectures Overcomplete Convolutional Network Kite-Net (Kite-Net), Attention gate mechanism is an improvement added on convolutional network architecture for fast and precise segmentation of images (Attention U-Net), Harmony Densely Connected Network-Medical image Segmentation (HarDNet-MSEG). In this regard, we will create a comprehensive computer assisted diagnostic methodology validated by a randomized controlled clinical trial. The model will be a highly automated tool for diagnosing and staging precancers and cervical cancer and thyroid cancers. This would help drastically minimize the time and effort that specialists put into analyzing medical images, help to achieve a better therapeutic plan, and can provide a “second opinion” of computer assisted diagnosis.
文摘Many datasets in E-commerce have rich information about items and users who purchase or rate them. This information can enable advanced machine learning algorithms to extract and assign user sentiments to various aspects of the items thus leading to more sophisticated and justifiable recommendations. However, most Collaborative Filtering (CF) techniques rely mainly on the overall preferences of users toward items only. And there is lack of conceptual and computational framework that enables an understandable aspect-based AI approach to recommending items to users. In this paper, we propose concepts and computational tools that can sharpen the logic of recommendations and that rely on users’ sentiments along various aspects of items. These concepts include: The sentiment of a user towards a specific aspect of a specific item, the emphasis that a given user places on a specific aspect in general, the popularity and controversy of an aspect among groups of users, clusters of users emphasizing a given aspect, clusters of items that are popular among a group of users and so forth. The framework introduced in this study is developed in terms of user emphasis, aspect popularity, aspect controversy, and users and items similarity. Towards this end, we introduce the Aspect-Based Collaborative Filtering Toolbox (ABCFT), where the tools are all developed based on the three-index sentiment tensor with the indices being the user, item, and aspect. The toolbox computes solutions to the questions alluded to above. We illustrate the methodology using a hotel review dataset having around 6000 users, 400 hotels and 6 aspects.
基金supported in part by the JSPS-CAS Core University Program in the field of Plasma and Nuclear Fusion
文摘Recent experimental progress in JT-60U advanced tokamak research is presented： sustainment of the normalized beta （βN）- 3 in a normal magnetic shear plasma, the bootstrap current fraction （fBs） - 45% in a weak shear plasma and - 75% in a reversed magnetic shear plasma in a nearly fully non-inductive current drive condition for longer than the current relaxation time. Achievement of high-density, high-radiation fraction together with high-confinement in advanced plasmas is demonstrated. Achievements and findings in long pulse operations after system modification are presented as well. A 65 s discharge of Ip = 0.7 MA was successfully obtained. As a result, high-βN of 2.3 was successfully sustained for a very long period of 22.3 s. In addition, a 30 s standard ELMy H-mode plasma of Ip up to 1.4 MA was also obtained. Effectiveness of divertor pumping to control particle recycling and the electron density under the saturated wall retention was demonstrated. These achievements and issues in development are discussed.
文摘Probiotification of plant milk can improve its sensory and health-promoting properties. As traditional fermented foods where lactic acid bacteria (LAB) are present have been associated with beneficial effects on human health, the beneficial effects of two LAB recently isolated from two current Ivorian staple foods (a pepper and a traditional beer) were screened. These two strains LAC 1 (Lactobacillus plantarum) and LAC 2 (Pediococcus acidilactici) which presented probiotic, exopolysaccharides, inflammatory and anti-oxidant activities, were used to ferment a composite plant milk of tiger-nut and cashew (80/20) compared to two starters of a commercial yogourt. The obtained plant milks SCT 2 and SCT 3 with a significant increase in their antioxidant and/or anti-inflammatory activities and lactic bacteria contents were more preferred by consumers than SCT 1 obtained by fermentation of the commercial yogourt starters. The mixing of LAC 1 and LAC 2 was not beneficial. SCT 2 (with an anti-inflammatory activity of 31.38% and an anti-oxidant activity of 17.30%) and SCT 3 (with an anti-oxidant activity of 22.28) could be further tested in animal models to verify their nutrition-health claims.
文摘<div style="text-align:justify;"> <span style="line-height:1.5;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">Pathologies transmissible by hand such as gastrointestinal pathologies constitute a real public health problem, especially in sub-Saharan Africa where hygienic conditions are precarious. This study took place at Félix Houphou</span><span style="white-space:nowrap;font-family:Verdana;">ë</span><span style="font-family:Verdana;"></span></span><span style="font-family:Verdana;">t-Boigny</span></span><span "="" style="line-height:1.5;"><span style="font-family:Verdana;"> University from April to August 2018. The samples were taken from toilet surfaces such as doorknobs, tap heads, flush push buttons and seats WC. A total of three hundred and sixty-eight (368) samples were obtained, including 170 from the staff toilets and 198 from the student toilets. The results revealed the presence of total coliforms, </span><i><span style="font-family:Verdana;">Escherichia</span></i><span style="font-family:Verdana;"> spp and </span><i><span style="font-family:Verdana;">Salmonella</span></i><span style="font-family:Verdana;"><span style="font-family:Verdana;"> spp. The surfaces of student toilets were the most contaminated surfaces. The presence of entero-bacteria on the contact surfaces of the toilets of the Félix Houphou</span><span style="white-space:nowrap;font-family:Verdana;">ë</span><span style="font-family:Verdana;"></span></span><span style="font-family:Verdana;">t-Boigny university represents a health risk for the university population.</span></span> </div>
文摘The decrease of fertility soils, the rarity of quality potting soil used to fill nursery bags, the high cost of chemical fertilisers and the problems associated with their use are leading planters and rubber nurserymen in developing and/or expanding areas to look for alternative and sustainable fertilization. In this perspective, a trial was carried out at Research Station of CNRA-Bimbresso and in a farmer’s environment in order to evaluate the agronomic quality of compost made from chicken droppings and dry <em>Panicum maximum</em> straw to improve the growth of rubber plants in bagged nurseries. Mixtures based on potting soil and/or compost in different proportions were prepared. The follow-up of the trial focused on determination of the physico-chemical characteristics of the soils, measurement of the parameters of vegetative growth and the grafting success rate evaluation of rubber plants in nursery. The results obtained show that compost-based crop substrates increase soil organic matter, nitrogen, exchangeable bases, etc., in proportion to the doses applied. For the pH, the application of compost resulted in a reduction in soil acidity of about 1.3 unit compared to the initial values at the two study sites. The vegetative behaviour of the rubber plants also shows that qualitative (height and collar diameter) and quantitative (grafting success rate) improvements were recorded in the plants raised in compost-based substrates. The production of rubber plants in bagged nurseries was optimal with compost doses of 27 t<span style="white-space:nowrap;">⋅</span>ha<sup><span style="white-space:nowrap;">−</span>1</sup> (at Bimbresso, in the southeast) and 27 t<span style="white-space:nowrap;">⋅</span>ha<sup><span style="white-space:nowrap;">−</span>1</sup> combined with fractionated application of urea (at Kimoukro, in the centre), which under the conditions of the present study may be the recommended doses on rubber plants in bagged nurseries at C<span style="white-space:nowrap;">ô</span>te d’Ivoire.
