This article describes a pilot study aiming at generating social interactions between a humanoid robot and adolescents with autism spectrum disorder (ASD), through the practice of a gesture imitation game. The partici...This article describes a pilot study aiming at generating social interactions between a humanoid robot and adolescents with autism spectrum disorder (ASD), through the practice of a gesture imitation game. The participants were a 17-year-old young lady with ASD and intellectual deficit, and a control participant: a preadolescent with ASD but no intellectual deficit (Asperger syndrome). The game is comprised of four phases: greetings, pairing, imitation, and closing. Field educators were involved, playing specific roles: visual or physical inciter. The use of a robot allows for catching the participants’ attention, playing the imitation game for a longer period of time than with a human partner, and preventing the game partner’s negative facial expressions resulting from tiredness, impatience, or boredom. The participants’ behavior was observed in terms of initial approach towards the robot, positioning relative to the robot in terms of distance and orientation, reactions to the robot’s voice or moves, signs of happiness, and imitation attempts. Results suggest a more and more natural approach towards the robot during the sessions, as well as a higher level of social interaction, based on the variations of the parameters listed above. We use these preliminary results to draw the next steps of our research work as well as identify further perspectives, with this aim in mind: improving social interactions with adolescents with ASD and intellectual deficit, allowing for better integration of these people into our societies.展开更多
Several socio-environmental needs(medicine,industry,engineering,orogenesis,genesis,etc.)require minerals to be more precisly defined and characterised.The identification of minerals plays a crucial role for researcher...Several socio-environmental needs(medicine,industry,engineering,orogenesis,genesis,etc.)require minerals to be more precisly defined and characterised.The identification of minerals plays a crucial role for researchers and is becoming an essential aspect of geological analysis.However,traditional methods relied heavily on expert knowledge and specialised equipment,making them labour-intensive,costly and time-consuming.This depen-dence is often labour-intensive,not to mention costly and time-consuming.To address this issue,some re-searchers have opted for machine learning algorithms to quickly identify a single mineral in a microscopic image of rocks.However this approch does not correspond to patterns of mineral distribution,where minerals are typically found in associations.These associations make it difficult to accurately identify minerals using con-ventional machine learning algorithms.This paper introduces a deep neural learning model based on multi-label classification,utilizing the problem adaptation method to analyse microscopic images of rock thin sections.The model is based on the ResNet50 architecture,which is designed to analyse minerals and generates the probability of a mineral presence in an image.This method provides a solution to the dependence between associated minerals.Experiments on many test images showed a model confidence,achieving average precision,recall and F1_score 97.15%,96.25%and 96.69%,respectively.Visualisation of the class activation mapping using the Grad-CAM algorithm indicates that our model is likely to locate the identified minerals effectively.In this way,the importance of each pixel with the class of interest can be assessed using heat maps.The recorded results,in terms of both performance and pixel_level evaluation,demonstrate the promising potential of the model used.It can therefore be considered for multi-labels image classification,particulary for images representing rock minerals.This approach serves as a valuable support tool for geological studies.展开更多
This paper deals with an abstract periodic gradient system in which the gradient is taken with respect to a variable metric. We obtain an existence and uniqueness result via the application of a global inverse theorem.
In this paper, we introduce and study a method for the numerical solution of the elliptic Monge-Ampere equation with Dirichlet boundary conditions. We formulate the Monge-Ampere equation as an optimization problem. Th...In this paper, we introduce and study a method for the numerical solution of the elliptic Monge-Ampere equation with Dirichlet boundary conditions. We formulate the Monge-Ampere equation as an optimization problem. The latter involves a Poisson Problem which is solved by the finite element Galerkin method and the minimum is computed by the conjugate gradient algorithm. We also present some numerical experiments.展开更多
In addition to the cashew nut, which is the main product, the cashew tree also produces the cashew apple which is considered a by-product. The cashew apple has a high nutritional potential. Indeed, it is rich in vitam...In addition to the cashew nut, which is the main product, the cashew tree also produces the cashew apple which is considered a by-product. The cashew apple has a high nutritional potential. Indeed, it is rich in vitamin C, carotenoids, dietary fibers, vitamins, sugars and mineral elements where are essential for human nutrition. In addition to its nutritional quality, the cashew apple has technological advantages: the edible part of the fruit is between 85% and 100% higher than that of other traditional tropical fruits, and its juicy and sweet flesh is free of seeds or pits. In addition, very large volumes are available. As a result, the development of this fruit represents a considerable economic challenge. This paper first presents the cultivation of cashew trees and the bibliography of the work done on cashew juice. The favorable conditions for cashew tree cultivation and the planting method were presented. Then, the study highlights the work done on the physicochemical characteristics of cashew apples, the effect of the growing area, the variety and the stage of maturity on its characteristics. It also shows the influence of the processing steps on the nutritional value and organoleptic quality of the cashew apple;as well as the methods of clarification, stabilization, concentration and dehydration. Some uses of cashew apple were reviewed: beverage, food, substrate, bioethanol, nutraceutical, food additive and agro materials.展开更多
The objective of this study is to analyze the sensitivity of the statistical models regarding the size of samples. The study carried out in Ivory Coast is based on annual maximum daily rainfall data collected from 26 ...The objective of this study is to analyze the sensitivity of the statistical models regarding the size of samples. The study carried out in Ivory Coast is based on annual maximum daily rainfall data collected from 26 stations. The methodological approach is based on the statistical modeling of maximum daily rainfall. Adjustments were made on several sample sizes and several return periods (2, 5, 10, 20, 50 and 100 years). The main results have shown that the 30 years series (1931-1960;1961-1990;1991-2020) are better adjusted by the Gumbel (26.92% - 53.85%) and Inverse Gamma (26.92% - 46.15%). Concerning the 60-years series (1931-1990;1961-2020), they are better adjusted by the Inverse Gamma (30.77%), Gamma (15.38% - 46.15%) and Gumbel (15.38% - 42.31%). The full chronicle 1931-2020 (90 years) presents a notable supremacy of 50% of Gumbel model over the Gamma (34.62%) and Gamma Inverse (15.38%) model. It is noted that the Gumbel is the most dominant model overall and more particularly in wet periods. The data for periods with normal and dry trends were better fitted by Gamma and Inverse Gamma.展开更多
In this paper, the heat, resolvent and wave kernels associated to the Schr?dinger operator with multi-inverse square potential on the Euclidian space Rn are given in explicit forms.
Leadership succession in nursing academic programs poses a significant challenge, primarily due to the limited availability of professionals with the competencies required for effective leadership [1]. This study aims...Leadership succession in nursing academic programs poses a significant challenge, primarily due to the limited availability of professionals with the competencies required for effective leadership [1]. This study aims to address this gap by investigating the critical factors in succession planning for nursing program administrators. The research objectives include identifying the competencies necessary for academic administrators, assessing the experience of current administrators, and developing a comprehensive succession plan framework. The research uses qualitative methods, including literature review, interviews with nursing administrators, and analysis of existing succession models. Results highlight the importance of integrating strategic planning into succession processes to ensure smooth transitions and organizational stability. Conclusions suggest that a formalized succession plan, incorporating mentorship and leadership development, can mitigate leadership gaps in nursing academia [2].展开更多
Baggage screening is crucial for airport security. This paper examines various algorithms for firearm detection in X-ray images of baggage. The focus is on identifying steel barrel bores, which are essential for deton...Baggage screening is crucial for airport security. This paper examines various algorithms for firearm detection in X-ray images of baggage. The focus is on identifying steel barrel bores, which are essential for detonation. For this, the study uses a set of 22,000 X-ray scanned images. After preprocessing with filtering techniques to improve image quality, deep learning methods, such as Convolutional Neural Networks (CNNs), are applied for classification. The results are also compared with Autoencoder and Random Forest algorithms. The results are validated on a second dataset, highlighting the advantages of the adopted approach. Baggage screening is a very important part of the risk assessment and security screening process at airports. Automating the detection of dangerous objects from passenger baggage X-ray scanners can speed up and increase the efficiency of the entire security procedure.展开更多
文摘This article describes a pilot study aiming at generating social interactions between a humanoid robot and adolescents with autism spectrum disorder (ASD), through the practice of a gesture imitation game. The participants were a 17-year-old young lady with ASD and intellectual deficit, and a control participant: a preadolescent with ASD but no intellectual deficit (Asperger syndrome). The game is comprised of four phases: greetings, pairing, imitation, and closing. Field educators were involved, playing specific roles: visual or physical inciter. The use of a robot allows for catching the participants’ attention, playing the imitation game for a longer period of time than with a human partner, and preventing the game partner’s negative facial expressions resulting from tiredness, impatience, or boredom. The participants’ behavior was observed in terms of initial approach towards the robot, positioning relative to the robot in terms of distance and orientation, reactions to the robot’s voice or moves, signs of happiness, and imitation attempts. Results suggest a more and more natural approach towards the robot during the sessions, as well as a higher level of social interaction, based on the variations of the parameters listed above. We use these preliminary results to draw the next steps of our research work as well as identify further perspectives, with this aim in mind: improving social interactions with adolescents with ASD and intellectual deficit, allowing for better integration of these people into our societies.
文摘Several socio-environmental needs(medicine,industry,engineering,orogenesis,genesis,etc.)require minerals to be more precisly defined and characterised.The identification of minerals plays a crucial role for researchers and is becoming an essential aspect of geological analysis.However,traditional methods relied heavily on expert knowledge and specialised equipment,making them labour-intensive,costly and time-consuming.This depen-dence is often labour-intensive,not to mention costly and time-consuming.To address this issue,some re-searchers have opted for machine learning algorithms to quickly identify a single mineral in a microscopic image of rocks.However this approch does not correspond to patterns of mineral distribution,where minerals are typically found in associations.These associations make it difficult to accurately identify minerals using con-ventional machine learning algorithms.This paper introduces a deep neural learning model based on multi-label classification,utilizing the problem adaptation method to analyse microscopic images of rock thin sections.The model is based on the ResNet50 architecture,which is designed to analyse minerals and generates the probability of a mineral presence in an image.This method provides a solution to the dependence between associated minerals.Experiments on many test images showed a model confidence,achieving average precision,recall and F1_score 97.15%,96.25%and 96.69%,respectively.Visualisation of the class activation mapping using the Grad-CAM algorithm indicates that our model is likely to locate the identified minerals effectively.In this way,the importance of each pixel with the class of interest can be assessed using heat maps.The recorded results,in terms of both performance and pixel_level evaluation,demonstrate the promising potential of the model used.It can therefore be considered for multi-labels image classification,particulary for images representing rock minerals.This approach serves as a valuable support tool for geological studies.
文摘This paper deals with an abstract periodic gradient system in which the gradient is taken with respect to a variable metric. We obtain an existence and uniqueness result via the application of a global inverse theorem.
文摘In this paper, we introduce and study a method for the numerical solution of the elliptic Monge-Ampere equation with Dirichlet boundary conditions. We formulate the Monge-Ampere equation as an optimization problem. The latter involves a Poisson Problem which is solved by the finite element Galerkin method and the minimum is computed by the conjugate gradient algorithm. We also present some numerical experiments.
文摘In addition to the cashew nut, which is the main product, the cashew tree also produces the cashew apple which is considered a by-product. The cashew apple has a high nutritional potential. Indeed, it is rich in vitamin C, carotenoids, dietary fibers, vitamins, sugars and mineral elements where are essential for human nutrition. In addition to its nutritional quality, the cashew apple has technological advantages: the edible part of the fruit is between 85% and 100% higher than that of other traditional tropical fruits, and its juicy and sweet flesh is free of seeds or pits. In addition, very large volumes are available. As a result, the development of this fruit represents a considerable economic challenge. This paper first presents the cultivation of cashew trees and the bibliography of the work done on cashew juice. The favorable conditions for cashew tree cultivation and the planting method were presented. Then, the study highlights the work done on the physicochemical characteristics of cashew apples, the effect of the growing area, the variety and the stage of maturity on its characteristics. It also shows the influence of the processing steps on the nutritional value and organoleptic quality of the cashew apple;as well as the methods of clarification, stabilization, concentration and dehydration. Some uses of cashew apple were reviewed: beverage, food, substrate, bioethanol, nutraceutical, food additive and agro materials.
文摘The objective of this study is to analyze the sensitivity of the statistical models regarding the size of samples. The study carried out in Ivory Coast is based on annual maximum daily rainfall data collected from 26 stations. The methodological approach is based on the statistical modeling of maximum daily rainfall. Adjustments were made on several sample sizes and several return periods (2, 5, 10, 20, 50 and 100 years). The main results have shown that the 30 years series (1931-1960;1961-1990;1991-2020) are better adjusted by the Gumbel (26.92% - 53.85%) and Inverse Gamma (26.92% - 46.15%). Concerning the 60-years series (1931-1990;1961-2020), they are better adjusted by the Inverse Gamma (30.77%), Gamma (15.38% - 46.15%) and Gumbel (15.38% - 42.31%). The full chronicle 1931-2020 (90 years) presents a notable supremacy of 50% of Gumbel model over the Gamma (34.62%) and Gamma Inverse (15.38%) model. It is noted that the Gumbel is the most dominant model overall and more particularly in wet periods. The data for periods with normal and dry trends were better fitted by Gamma and Inverse Gamma.
文摘In this paper, the heat, resolvent and wave kernels associated to the Schr?dinger operator with multi-inverse square potential on the Euclidian space Rn are given in explicit forms.
文摘Leadership succession in nursing academic programs poses a significant challenge, primarily due to the limited availability of professionals with the competencies required for effective leadership [1]. This study aims to address this gap by investigating the critical factors in succession planning for nursing program administrators. The research objectives include identifying the competencies necessary for academic administrators, assessing the experience of current administrators, and developing a comprehensive succession plan framework. The research uses qualitative methods, including literature review, interviews with nursing administrators, and analysis of existing succession models. Results highlight the importance of integrating strategic planning into succession processes to ensure smooth transitions and organizational stability. Conclusions suggest that a formalized succession plan, incorporating mentorship and leadership development, can mitigate leadership gaps in nursing academia [2].
文摘Baggage screening is crucial for airport security. This paper examines various algorithms for firearm detection in X-ray images of baggage. The focus is on identifying steel barrel bores, which are essential for detonation. For this, the study uses a set of 22,000 X-ray scanned images. After preprocessing with filtering techniques to improve image quality, deep learning methods, such as Convolutional Neural Networks (CNNs), are applied for classification. The results are also compared with Autoencoder and Random Forest algorithms. The results are validated on a second dataset, highlighting the advantages of the adopted approach. Baggage screening is a very important part of the risk assessment and security screening process at airports. Automating the detection of dangerous objects from passenger baggage X-ray scanners can speed up and increase the efficiency of the entire security procedure.
