Brain tumor is formed by the uncontrolled growth of cancerous (malign) or non-cancerous (benign) unhealthy cells in the brain. In the present world brain tumor is a very dangerous disease and the main reason for many ...
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In today’s dynamic healthcare environment an efficient allocation of healthcare resources is essential for overall positive outcomes of healthcare processes and patient’s satisfaction. A preliminary stage for moving...
In today’s dynamic healthcare environment an efficient allocation of healthcare resources is essential for overall positive outcomes of healthcare processes and patient’s satisfaction. A preliminary stage for moving towards an efficient allocation of resources is the existence of an Integrated Management System (IMS) in the healthcare organizations. An IMS consist in a series of requirements on different areas that are mandatory to be *** modeling tools have been developed to improve the current state of healthcare processes. Those models can aid the decision-making process for allocation of healthcare resources and reduce costs. The purpose of this article is to present a predictive framework for efficient allocation in the healthcare system organization with implemented IMS. Type of resources relevant in the proposed framework were selected based on Pareto’s rule. The aim of the predictive framework is to support better allocation and management of healthcare resources, which is critical for reliable healthcare outcomes. The framework integrates value-based concepts and it is focused on finding balance between process performance and cost.
In the paper, the authors check the behaviour of Bluetooth Low Energy protocol in a popular smart wristband and a microcontroller in the heart rate monitoring application. The measurements were collected using a devel...
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In the paper, the authors check the behaviour of Bluetooth Low Energy protocol in a popular smart wristband and a microcontroller in the heart rate monitoring application. The measurements were collected using a development board with the ESP32 System on Chip. The authors tested measurement period stability and measurement reliability in various conditions.
Nowadays, we can observe a growing interest in sustainable buildings. Sustainable development cannot be achieved without introducing innovations in green building;therefore, innovations are important component of sust...
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The paper presents a solution for holonic control of smart manufacturing systems, using a mix of digitization procedures that capitalize on the possibilities offered by a Digital Twin simulation environment in modelin...
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In this paper, we propose a genetic algorithm based on behavioral psychology developed by Carl Gustav Jung (16 Personalities model), in which we describe the person's behavioral features related to his personality...
In this paper, we propose a genetic algorithm based on behavioral psychology developed by Carl Gustav Jung (16 Personalities model), in which we describe the person's behavioral features related to his personality. The model used for inherence is based on 40 years of psychology studies from the book “The 16personalityy types that determinate how we live, love and work” [1] by Otto Kroeger and Janet M. Thuesen, published in 1988, but using inference extracted from an MBTI (Myers-Briggs Personality Type Indicator) dataset of online posts based on person personality and it thinks from 2018 [2].
This review aims to contribute to the quest for artificial general intelligence by examining neuroscience and cognitive psychology methods for potential inspiration. Despite the impressive advancements achieved by dee...
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作者：
Urszula StańczykDepartment of Computer Graphics
Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 2A 44-100 Gliwice Poland
In the context of data imbalance probably the most investigated problem is imbalance of classes, as learning from the data with this characteristic makes detection of existing patterns for all classes more difficult. ...
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In the context of data imbalance probably the most investigated problem is imbalance of classes, as learning from the data with this characteristic makes detection of existing patterns for all classes more difficult. However, other problems related to imbalance also exists and the paper addresses such cases where classes are balanced, but there is in-class imbalance. Such imbalance can be caused by uneven representation of sub-concepts. When there is a noticeable difference between the numbers of samples belonging to sub-concepts, this can turn the under-represented sub-concepts into disjuncts. Data irregularities of this type can hinder recognition, therefore actions are typically taken to restore balance. In the investigations described, the issue was studied in the stylometric domain and various classifiers were applied to the data that was balanced, then imbalanced, and finally with restored balance. The experiments show that the specifics of the domain of application can put its own mark on the data which is difficult to overcome by standard processing such as under- or oversampling. Observed dependence on a learner and dataset makes the issue even more complex and layered, and shows the need for deeper studies.
The paper presents research dedicated to observations of relations between attribute properties and discretisation. In the investigations described, the gradually increasing sets of features were discretised by select...
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The paper presents research dedicated to observations of relations between attribute properties and discretisation. In the investigations described, the gradually increasing sets of features were discretised by selected approaches, and several variants of data were constructed. The continuous, partially discrete, and completely translated datasets were explored by the chosen classifiers and their performance studied in the context of a number of discretised attributes, discretisation procedures, and the way of processing of features and datasets. The stylometric problem of authorship attribution was the machine learning task under study. The experimental results enable to observe closer the specificity of style-markers employed as characteristic features, and indicate conditions for efficient recognition of authorship. They can be extended to other application domains with similar characteristics.
Using photovoltaic (PV) systems connected in distribution and even transport grids increase the need for energy supply security. Energy Efficiency of PV power plants is a performance indicator as well as a fault detec...
Using photovoltaic (PV) systems connected in distribution and even transport grids increase the need for energy supply security. Energy Efficiency of PV power plants is a performance indicator as well as a fault detection method. control system topologies for grid connected PV power plants can increase the overall generation performance. Three types of plant control topologies with their benefits and drawbacks are compared. The paper also synthesizes the control requirements for each of the plant components cells/panels, inverter and grid connection point. The PV panel faults issue is tackled practically by designing a PVPP test bed for further application of the proposed fault detection algorithm. A 80kW rooftop PV plant is proposed for efficiency evaluation. A decision tree algorithm for power plant efficiency and fault detection is designed. Computation of the capacity factor is an energy efficiency indicator, as well as a detector for PV panel fault initiation by dust or objects covering the cells. A hierarchical control system architecture with a central level PLC and 4 inverters, each with several MPPT modules, one for each string is proposed. The fault tree algorithm will be implemented on the practical PV power plant test bed.
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