Physicians are likely to expend significant labor and time while manually calculating blood smears. Automatic computer-based methods for classifying acute lymphoblastic leukemia have trouble correctly lighting stained white blood cell microscopy images and accurately separating cells that touch or overlap. Additionally, incorporating machine learning techniques into medical services is very hard because doctors can deal with rough guesses as long as the results aren't too bad, but they can't use these calculations for actual medical care. Enabling a A deep network having knowledge of the accuracy of its own predictions is a fascinating and crucial issue. Most instances segmentation frameworks weigh the mask quality during the instance

Recently, detecting dynamic patterns for growing communities in social networks have attracted significant attention. The objective of dynamic community detection is to analyze and identify clusters in complex networks that change over time. Different optimization algorithms, including both single-objective and multi-objective approaches, have been employed to address the challenge of dynamic community detection. Although current evolutionary algorithms for identifying community structure can traverse extensive areas of partition space, they often become stuck in local minima. In addition, limited studies have addressed this issue by integrating local search strategies with evolutionary algorithms for community identification. This paper in

This work presents a canned-food defect-detection method using the EfficientDet model with four backbones (MobileNet, EfficientNet, Swin-T, and ConvNeXt). The dataset included 8046 images with a resolution of 512 × 512 pixels. The performance criteria in this study accuracy “mAP”, computational cost “FLOPs”, and Frames Per Second “FPS”. The lightweight backbone with EfficientDet achieves a mean Average Precision (mAP) of 90% with MobileNet, while EfficientNet achieves mAP accuracy of 92% and 94%. The heavy backbone for EfficientDet (Swin-T, and ConvNeXt) achieves mAP accuracy of 96% and 98%. The main contribution of this study is to optimize the speed of conveyor belts in industrial production lines to considers the

يمثل الأخذ بالنظام الفيدرالي أطاراً تنظيمياً لشكل الدولة و مرحلة تحول مهمة في بنية الدولة العامة في مختلف مجالاتها، فالانتقال من المركزية في أدارة الشؤون العامة للدولة الى النمط الفيدرالي يمثل تحولا بنيوياً وسيكولوجياً ،حيث يكون هنالك توزيع مكاني - عمودي للسلطة والثروة بين الوحدات المكونة للدولة بشكل يختلف كليا عن الحالة المركزية، ونجد صور تنظيمية عديدة تتأسس ضمن اطار الفيدرالية العام ،

Digital Models of Elevations (DEMs) Using Surfer 16, which are interpolated to create three-dimensional controls for the entire terrain, are typically used in visualization of geospatial entities. The interpolation method used determines how accurate the resulting terrain model will be, hence it is necessary to compare the effectiveness of various approaches in this situation. Numerous generic interpolation techniques, using inverse distance to a power, triangulation as with linear interpolation, the nearest neighbor, and kriging, have been studied. These interpolation techniques produced DEMs. With the aid of SURFER software 16, the primary goal of this effort was to introduce the DEM using a spatial interpolation method and to pre

Cancer is one of the dangerous diseases that afflict a person through injury to cells and tissues in the body, where a person is vulnerable to infection in any age group, and it is not easy to control and multiply between cells and spread to the body. In spite of the great progress in medical studies interested in this aspect, the options for those with this disease are few and difficult, as they require significant financial costs for health services and for treatment that is difficult to provide.

This study dealt with the determinants of liver cancer by relying on the data of cancerous tumours taken from the Iraqi Center for Oncology in the Ministry of Health 2017. Survival analysis has been used as a m

Digital Models of Elevations (DEMs) Using Surfer 16, which are interpolated to create three-dimensional controls for the entire terrain, are typically used in visualization of geospatial entities. The interpolation method used determines how accurate the resulting terrain model will be, hence it is necessary to compare the effectiveness of various approaches in this situation. Numerous generic interpolation techniques, using inverse distance to a power, triangulation as with linear interpolation, the nearest neighbor, and kriging, have been studied. These interpolation techniques produced DEMs. With the aid of SURFER software 16, the primary goal of this effort was to introduce the DEM using a spatial interpolation method and to pre

Background: The integration of modern computer-aided design and manufacturing technologies in diagnosis, treatment planning, and appliance construction is changing the way in which orthodontic treatment is provided to patients. The aim of this study is to assess the validity of digital and rapid prototyped orthodontic study models as compared to their original stone models. Materials and methods: The sample of the study consisted of 30 study models with well-aligned, Angle Class I malocclusion. The models were digitized with desktop scanner to create digital models. Digital files were then converted to plastic physical casts using prototyping machine, which utilizes the fused deposition modeling technology. Polylactic acid polymer was chose

Producing pseudo-random numbers (PRN) with high performance is one of the important issues that attract many researchers today. This paper suggests pseudo-random number generator models that integrate Hopfield Neural Network (HNN) with fuzzy logic system to improve the randomness of the Hopfield Pseudo-random generator. The fuzzy logic system has been introduced to control the update of HNN parameters. The proposed model is compared with three state-ofthe-art baselines the results analysis using National Institute of Standards and Technology (NIST) statistical test and ENT test shows that the projected model is statistically significant in comparison to the baselines and this demonstrates the competency of neuro-fuzzy based model to produce