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International Conference on control Systems and computer science (CSCS)

作者： Ciprian-Ionut Nutescu Mariana Mocanu Faculty of Automatic Control and Computer Science University Politehnica Bucharest Bucharest Romania

In this paper, we proposed a genetic algorithm based on behavioral psychology developed by Carl Gustav Jung (16 Personalities model), in which we describe the person’s behavioral leisure and ludic behavioral features regarding his personality. The model used for inference is based on 40 years of psychology research and studies from the book “The 16 Personalities types that determinate how we live, love and work” by Otto Kroger and Janet M. Thuesen, published in 1988. To generate the leisure model, we are using genetic algorithms. To improve the leisure model, we are reinforcing it using weight-based fitness functions with inference extracted from the HappyDB dataset. In this dataset, persons around the world express the most valuable/happy moments in their life. The leisure model describes how they would prefer spending their time and how this will bring the most enjoyment and reward (human reward psychological model).

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Domain-specific data characteristics: A study on meaning of stylometric sub-concepts and in-class imbalance

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Procedia computer science 2024年 246卷 4421-4430页

作者： Urszula Stańczyk Department 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. 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.

关键词： Attribute domain Data irregularities Sub-concept Disjunct Pattern recognition Stylometry Authorship attribution

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BigFeat: Scalable and Interpretable Automated Feature Engineering Framework

BigFeat: Scalable and Interpretable Automated Feature Engine...

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2022 IEEE International Conference on Big Data, Big Data 2022

作者： Eldeeb, Hassan Amashukeli, Shota Elshawi, Radwa University of Tartu Institute of Computer Science Tartu Estonia Tanta University Faculty of Engineering Computers and Automatic Control Department Tanta Egypt

ISBN: (纸本)9781665480451

Feature engineering is a crucial step in building well-performing machine learning pipelines. However, manually constructing highly predictive features is time-consuming and requires domain knowledge. Although the research area of automated feature engineering has attracted much interest lately, both in academia and industry, the scalability and efficiency of the existing systems and tools are still practically unsatisfactory. This paper presents a scalable and interpretable automated feature engineering framework, BigFeat, that optimizes input features' quality to maximize the predictive performance according to a user-defined metric. BigFeat employs a dynamic feature generation and selection mechanism that constructs a set of expressive features that improve the prediction performance while retaining interpretability. Extensive experiments are conducted, and the results show that BigFeat provides superior performance compared to the state-of-the-art automated feature engineering framework, AutoFeat, on a wide range of datasets. We show that BigFeat significantly improves the F1-Score of 8 classifiers by 4.59%, on average. In addition, the performance improvement achieved by integrating BigFeat into different AutoML frameworks is higher than that achieved by integrating AutoFeat into the same frameworks. Besides, the scalability of BigFeat is confirmed by its linear complexity, parallel design, and execution time which is, on average, 22x faster than AutoFeat. © 2022 IEEE.

关键词： Scalability

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Observations of data characteristics and irregularities through domain-oriented transformations of attributes

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Procedia computer science 2024年 246卷 2694-2703页

作者： Urszula Stańczyk Grzegorz Baron Department 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

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.

关键词： Attribute domain Discretisation Data representation Data irregularities Pattern recognition Stylometry Authorship attribution

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Brown Marmorated Stink Bug Detection Using Multiple Neural Networks

Brown Marmorated Stink Bug Detection Using Multiple Neural N...

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Electrical, computer, Communications and Mechatronics Engineering (ICECCME), International Conference on

作者： Andrei Vicol Loretta Ichim Dan Popescu Faculty of Automatic Control and Computer Science University Politehnica of Bucharest Bucharest Romania

The identification and management of pest infestations in a timely manner have been an ever-pressing issue, more so than ever now, when new pests have arrived from around the world and governments are encouraging farmers to use fewer and fewer pesticides. The use of drones and artificial intelligence in the monitoring of orchards has taken a strong rise in recent years due to the advantages offered by efficiency, coverage, and price. A particularly dangerous insect in fruit production is the brown marmorated stink bug (BMSB). The paper seeks to look at a performance comparison in BMSB detection between three states of the art models of image detection and classification: MobileNetV2, Xception, and EfficientNet. Each network model was slightly modified being thus adapted for this application and the results obtained had high accuracy, between 97% and 99%.

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Segmentation of Brain Tumors from MRI Images Using Deep Neural Networks 23

Segmentation of Brain Tumors from MRI Images Using Deep Neur...

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23rd International Conference on control Systems and computer science Technologies, CSCS 2021

作者： Roznov, Andrei Dobrescu, Radu Popescu, Dan Ichim, Loretta University Politehnica of Bucharest Faculty of Automatic Control and Computer Science Bucharest Romania University Politehnica of Bucharest Institute of Virology Faculty of Automatic Control and Computer Science Bucharest Romania

ISBN: (纸本)9781665439398

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 deaths. Magnetic Resonance Imaging (MRI) is mostly used to produce medical images for the brain tumor analysis. This paper has two objectives, first one is to identify if the MRI images has or not brain tumor using Convolutional Neural Network algorithm based on ResNet50 architecture. For second objective, image segmentation, we propose a generalized focal loss function based on Tversky index. Compared to the commonly used Dice loss, the proposed loss function achieves better precision and recall when training on small structures such as lesions. © 2021 IEEE.

关键词： Image segmentation

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Output Tracking control of a Nonlinear System Based on Takagi-Sugeno Fuzzy Model: Generalized Partial Eigenstructure Assignment Approach

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IEEE Access 2024年 12卷 18520-18535页

作者： Soltanian, Farzad Shasadeghi, Mokhtar Mobayen, Saleh Skruch, Pawel University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2M9 Canada Shiraz University of Technology Electrical Engineering Faculty Shiraz71557-13876 Iran National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Yunlin Douliu64002 Taiwan AGH University of Science and Technology Department of Automatic Control and Robotics Kraków30-059 Poland

This paper introduces an innovative optimal control approach to achieve output tracking while incorporating H2-performance specifications in a specific class of nonlinear dynamics modeled by the Takagi-Sugeno fuzzy model (TSFM). The primary innovation lies in extending partial eigenstructure assignment to TSFM-based nonlinear systems within the framework of sliding mode control (SMC). We propose a two-step methodology for designing optimal sliding surface gains. Initially, optimal state feedback gains are computed for each rule consequence containing a linear subsystem, adhering to predetermined eigenvalues and satisfying H2-performance criteria. Subsequently, using a convex combination, the overall state feedback gain is calculated and utilized to design sliding matrix gains. The sliding matrix gains are then determined by strategically combining previously calculated state-feedback gains in a convex optimization problem. We reframe the output tracking strategy as a stabilization problem using a virtual control input and reformulate the optimization task concerning tracking state errors. This process yields state feedback gains, sliding gains, and the formulation of the virtual control input. The effectiveness of our approach is verified through comprehensive simulations, emphasizing its capability in addressing output tracking challenges within nonlinear systems. © 2013 IEEE.

关键词： Transient analysis

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Analog, Programmable Switched Capacitor FIR Filter Based on Rotator Architecture Implemented in CMOS Technology 26

Analog, Programmable Switched Capacitor FIR Filter Based on ...

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26th IEEE Signal Processing: Algorithms, Architectures, Arrangements, and Applications, SPA 2023

作者： Pawlowski, Pawel Dlugosz, Rafal Radkowski, Marek Watly, Mateusz Dabrowski, Adam Poznań University of Technology Division of Signal Processing and Electronic Systems Faculty of Control Robotics and Electrical Engineering Institute of Automatic Control and Robotics Poznań60-965 Poland Bydgoszcz University of Science and Technology Faculty of Telecommunication Computer Science and Electrical Engineering Bydgoszcz85-796 Poland

ISBN: (纸本)9798350304985

The paper presents project and its verification of a prototype integrated circuit containing an analog, programmable finite impulse response (FIR) filter, implemented in CMOS 350 nm technology. The structure of the filter is based on the switched capacitor technique. In circuits of this type, one of main challenges is an efficient implementation of filter coefficients, which result from several factors described in this work. When implementing such filters as programmable circuits, the values of their coefficients have to be limited to a selected range, i.e. a given resolution in bits. In the implemented prototype filter, the filter coefficients are represented by 6 bits in sign-magnitude notation, so they can take 63 different values only. In such filters, it is not possible to directly implement any frequency response of the filter. Each time, it is necessary to properly round the theoretical values of the coefficients so that they fit into the available range of discrete values resulting from the implementation. The authors of the work designed an algorithm that allows such matching. The paper also presents results of measurements of the prototype chip. © 2023 Division of Signal Processing and Electronic Systems, Poznan University of Technology (DSPES PUT).

关键词： FIR filters

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A Predictive Framework for Efficient Resources Allocation in Healthcare Organisations

A Predictive Framework for Efficient Resources Allocation in...

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International Conference on control Systems and computer science (CSCS)

作者： Gabriela Coman Ştefan Mocanu Radu Dobrescu Faculty of Automatic Control and Computer Science University Politehnica of Bucharest Bucharest Romania

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.

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A holonic approach of manufacturing systems modeling and simulation 23

A holonic approach of manufacturing systems modeling and sim...

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23rd International Conference on control Systems and computer science Technologies, CSCS 2021

作者： Cristescu, Giorgiana Chenaru, Oana Dobrescu, Radu Politehnica University Faculty of Automatic Control and Computer Science Bucharest Romania

ISBN: (纸本)9781665439398

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 modeling and simulating both the physical entities of the industrial plant and of the execution phases of the production process. The main novelty is the creation of software assets by encapsulating FBs in holon-type containers, which can be used both in the design phase and in the production control phase. The validation of the solution was performed on a mechatronic laboratory line, specialized for assembly and disassembly operations. © 2021 IEEE.

关键词： Flow control

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