Internet of Things: Underwater routing based on user’s health status for smart diving

Technological advancements affect everyday life; they benefited our daily routines, habits, and activities. Underwater diving is one of the most interesting and attractive activities for tourists worldwide but could be risky and challenging. When paths are not clear, diving might take additional time and effort leading to some health problems. Thus, providing divers with proper direction information to surf underwater can be useful and helpful. Also, monitoring diverse health statuses and alerting them in case of any undesirable condition can increase their safety. Smart devices such as mobiles, watches, sensor devices, cellular networks along with the Internet of Things (IoT) can all provide location-based services. Such services can help in providing the best path for the divers and monitor their health status during diving. This paper proposes a new underwater routing approach, called Underwater Routing for Smart Diving “URSD”, which provides divers with routing information to visit underwater cultural or natural resources and monitors their health status during the diving period. The URSD approach was simulated and compared with the shortest path. Results showed that the URSD helped divers to route within paths that have a larger number of nodes, furthermore, it could enhance and improve divers experience and help them mitigate underwater risks

Employing CNN ensemble models in classifying dental caries using oral photographs

Dental caries is arguably the most persistent dental condition that affects most people over their lives. Carious lesions are commonly diagnosed by dentists using clinical and visual examination along with oral radiographs. In many circumstances, dental caries is challenging to detect with photography and might be mistaken as shadows for various reasons, including poor photo quality. However, with the introduction of Artificial Intelligence and robotic systems in dentistry, photographs can be a helpful tool in oral epidemiological research for the assessment of dental caries prevalence among the population. It can be used particularly to create a new automated approach to calculate DMF (Decay, Missing, Filled) index score. In this paper, an autonomous diagnostic approach for detecting dental cavities in photos is developed using deep learning algorithms and ensemble methods. The proposed technique employs a set of pretrained models including Xception, VGG16, VGG19, and DenseNet121 to extract essential characteristics from photographs and to classify images as either normal or caries. Then, two ensemble learning methods, E- majority and E-sum, are employed based on majority voting and sum rule to boost the performances of the individual pretrained model. Experiments are conducted on 50 images with data augmentation for normal and caries images, the employed E-majority and E-sum achieved an accuracy score of 96% and 97%, respectively. The obtained results demonstrate the superiority of the proposed ensemble framework in the detection of caries. Furthermore, this framework is a step toward constructing a fully automated, efficient decision support system to be used in the dentistry area

Constructing A Scale Based on Dramatic Representation of The Sociological and Psychological Skills of Students with Autism Spectrum Disorders and Verifying Its Psychometric Properties

The current study aimed to construct a measure based on dramatization of the sociological and psychological skills of students with autism spectrum disorders, in light of the variables of gender and group (experimental and control), and to verify its psychometric characteristics. The sample of the study consisted of (50) male and female students with autism spectrum disorders who were selected in a simple random manner. The sample was distributed into two groups. The experimental group amounted to (25), and the control group amounted to (25). The results of the study showed that there were statistically significant differences at the significance level (? ? 0.05) in the students’ performance on the immediate post-measurement in favor of the experimental group, and there were no statistically significant differences at the significance level (? ? 0.05). ? ? 0.05) in the students' performance of the sociological and psychological skills between the two measurements; The immediate and post-deferred dimensions of the experimental group, which gives an indication of the effectiveness of the scale of the sociological skills of students with autism spectrum disorders, and the current study, based on several indicators extracted from the SPSS program, concluded that the scale of the current study was judged with honesty in data representation, as well as with a high level of stability

Constructing A Scale Based on Dramatic Representation of The Sociological and Psychological Skills of Students with Autism Spectrum Disorders and Verifying Its Psychometric Properties

The current study aimed to construct a measure based on dramatization of the sociological and psychological skills of students with autism spectrum disorders, in light of the variables of gender and group (experimental and control), and to verify its psychometric characteristics. The sample of the study consisted of (50) male and female students with autism spectrum disorders who were selected in a simple random manner. The sample was distributed into two groups. The experimental group amounted to (25), and the control group amounted to (25). The results of the study showed that there were statistically significant differences at the significance level (? ? 0.05) in the students’ performance on the immediate post-measurement in favor of the experimental group, and there were no statistically significant differences at the significance level (? ? 0.05). ? ? 0.05) in the students' performance of the sociological and psychological skills between the two measurements; The immediate and post-deferred dimensions of the experimental group, which gives an indication of the effectiveness of the scale of the sociological skills of students with autism spectrum disorders, and the current study, based on several indicators extracted from the SPSS program, concluded that the scale of the current study was judged with honesty in data representation, as well as with a high level of stability

Predictive factors and adverse perinatal outcomes associated with maternal smoking status

Abstract To identify risk factors for smoking among pregnant women, and adverse perinatal outcomes among pregnant women. A case–control study of singleton full-term pregnant women who gave birth at a university hospital in Jordan in June 2020. Pregnant women were divided into three groups according to their smoking status, active, passive, and non-smokers. They were interviewed using a semi-structured questionnaire that included demographic data, current pregnancy history, and neonatal outcomes. Low-level maternal education, unemployment, secondary antenatal care, and having a smoking husband were identified as risk factors for smoke exposure among pregnant women. The risk for cesarean section was ninefold higher in nulliparous smoking women. Women with low family income, those who did not receive information about the hazards of smoking, unemployed passive smoking women, and multiparty raised the risk of neonatal intensive care unit admission among active smoking women. This risk increased in active and passive women with lower levels of education, and inactive smoking women with low family income by 25 times compared to women with a higher level of education. Smoking is associated with adverse perinatal outcomes. Appropriate preventive strategies should address modifiable risk factors for smoking during pregnancy

Elección de un método adecuado de priorización de requisitos: un estudio

Software requirements prioritization plays a crucial role in software development. It can be viewed as the process of ordering requirements by determining which requirements must be done first and which can be done later. Powerful requirements prioritization techniques are of paramount importance to finish the implementation on time and within budget. Many factors affect requirement prioritization such as stakeholder expectations, complexity, dependency, scalability, risk, and cost. Therefore, finding the proper order of requirements is a challenging process. Hence, different types of requirements prioritization techniques have been developed to support this task. In this survey, we propose a novel classification that can classify the prioritization techniques under two major classes: relative and exact prioritization techniques class, where each class is divided into two subclasses. We depend in our classification on the way the value of ranking is given to the requirement, either explicitly as a specific value in the case of the exact prioritization techniques class, or implicitly in the case of the Relative prioritization technique class. An overview of fifteen different requirements prioritization techniques are presented and organized according to the proposed classification criteria’s. Moreover, we make a comparison between methods that are related to the same subclass to analyze their strengths and weaknesses. Based on the comparison results, the properties for each proposed subclass of techniques are identified. Depending on these properties, we present some recommendations to help project managers in the process of selecting the most suitable technique to prioritize requirements based on their project characteristics (number of requirements, time, cost, and accuracy).La priorización de requisitos de software desempeña un papel crucial en el desarrollo de software. Puede verse como el proceso de ordenar los requisitos determinando cuáles deben hacerse primero y cuáles pueden hacerse después. Unas técnicas potentes de priorización de requisitos son de vital importancia para terminar la implementación a tiempo y sin salirse del presupuesto. Muchos factores afectan a la priorización de requisitos, como las expectativas de las partes interesadas, la complejidad, la dependencia, la escalabilidad, el riesgo y el coste. Por lo tanto, encontrar el orden adecuado de los requisitos es un proceso difícil. De ahí que se hayan desarrollado distintos tipos de técnicas de priorización de requisitos para apoyar esta tarea. En este estudio, proponemos una clasificación novedosa que puede clasificar las técnicas de priorización en dos clases principales: clase de técnicas de priorización relativa y clase de técnicas de priorización exacta, donde cada clase se divide en dos subclases. En nuestra clasificación dependemos de la forma en que se da el valor de clasificación al requisito, ya sea explícitamente como un valor específico en el caso de la clase de técnicas de priorización exacta, o implícitamente en el caso de la clase de técnicas de priorización relativa. Se presenta una visión general de quince técnicas diferentes de priorización de requisitos, organizadas según los criterios de clasificación propuestos. Además, se realiza una comparación entre métodos relacionados con la misma subclase para analizar sus puntos fuertes y débiles. A partir de los resultados de la comparación, se identifican las propiedades de cada subclase de técnicas propuesta. En función de estas propiedades, presentamos algunas recomendaciones para ayudar a los gestores de proyectos en el proceso de selección de la técnica más adecuada para priorizar requisitos en función de las características del proyecto (número de requisitos, tiempo, coste y precisión).Facultad de Informátic