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Wyniki wyszukiwania dla: LOGISTIC REGRESSION
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Assessment of wastewater quality indicators for wastewater treatment influent using an advanced logistic regression model
PublikacjaInfluent quality indicators play a significant role in wastewater treatment plant performance due to their correlation with reactor operations and effluent quality. However, selecting a specific/best parameter indicator for predicting influent wastewater quality is one of the challenges in wastewa- ter treatment. This study, therefore, focused on determining suitable variables as influent quality indicators. For this purpose, a...
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Application of Multinomial Logistic Regression to Model the Impact of Rainfall Genesis on the Performance of Storm Overflows: Case Study
PublikacjaIn this study, a mathematical model was proposed to analyze the performance of storm overfows. The model included the infuence of rainfall genesis on the duration of storm overfow, its volume, and the maximum instantaneous fow. The multinomial logistic regression model, which has not been used so far to model objects located in a stormwater system, was proposed to simulate the duration of storm overfow. The Iman–Conover method,...
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Factors affecting low-temperature cracking of asphalt pavements: analysis of field observations using the ordered logistic model
PublikacjaAccurate identification of factors that primarily affect the number of low-temperature cracks is crucial for selection of road materials and planning of pavement maintenance. Field investigations of lowtemperature cracks were performed in the years 2014 and 2020 on the same 68 road sections being in service in typical traffic conditions. The collected data were statistically analysed using the ordered logistic regression model....
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Usefulness of chest perfusion computed tomography in the diagnosis of diabetic pulmonary microangiopathy
PublikacjaThis paper presents the usefulness of perfusion computed tomography (pCT) in the diagnosis of diabetic pulmonary microangiopathy. Our previous works have shown that perfusion parameters are useful in the diagnosis of diabetic pulmonary microangiopathy. We are looking for such measurements and perfusion parameters that provide the most accurate diagnosis. Two types of comparison were made based on the results of clinical trials:...
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Application of Multivariate Analysis Methods in Welding Engineering
PublikacjaPhenomena and processes taking place during welding are usually very complex and, for this reason, should be described using multivariate methods. The article discusses the methodological basis and selected application areas as regards the solving of welding problems using statistical multivariate methods. In addition, the article presents exemplary applications of the design of experiment, multiple regression analysis, cluster...
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Lung perfusion parameters in the diagnosis of diabetic pulmonary microangiopathy
PublikacjaThis paper presents the role of perfusion computed tomography (pCT) in the diagnosis of diabetic pulmonary microangiopathy. Our previous works have shown that perfusion parameters are useful in the diagnosis of diabetic pulmonary microangiopathy. In this article we focus on conditions that are necessary for such the diagnosis and introduce method of classification no microangiopathy vs. microangiopathy based on logistic regression....
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When Neural Networks Meet Decisional DNA: A Promising New Perspective for Knowledge Representation and Sharing
PublikacjaABSTRACT In this article, we introduce a novel concept combining neural network technology and Decisional DNA for knowledge representation and sharing. Instead of using traditional machine learning and knowledge discovery methods, this approach explores the way of knowledge extraction through deep learning processes based on a domain’s past decisional events captured by Decisional DNA. We compare our approach with kNN (k-nearest...
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Advanced sensitivity analysis of the impact of the temporal distribution and intensity of rainfall on hydrograph parameters in urban catchments
PublikacjaKnowledge of the variability of the hydrograph of outflow from urban catchments is highly important for measurements and evaluation of the operation of sewer networks. Currently, hydrodynamic models are most frequently used for hydrograph modeling. Since a large number of their parameters have to be identified, there may be problems at the calibration stage. Hence, sensitivity analysis is used to limit the number of parameters....
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Determinants of COVID-19 Impact on the Private Sector: A Multi-Country Analysis Based on Survey Data
PublikacjaOur paper aims to investigate the impact of COVID‐19 on private sector companies in terms of sales, production, finance and employment. We check whether the country and industry in which companies operate, government financial support and loan access matter to the behaviour and performances of companies during the pandemic. We use a microdata set from a worldwide survey of more than 15,729 companies conducted between April and...
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User-assisted methodology targeted for building structure interpretable QSPR models for boosting CO2 capture with ionic liquids
PublikacjaTask-specific ionic liquid (IL) is an emerging class of compounds that may be environmentally friendly. Properly selected, these compounds may be green alternative to amine solutions and can replace them in post-combustion carbon dioxide (CO2) capture processes on an industrial scale. However, owing to the vast diversity of ions and their possible combinations, laboratory research is time consuming and expensive. Therefore, computational...
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Harnessing digital technologies for poverty reduction. Evidence for low-income and lower-middle income countries
PublikacjaThis paper contributes to understanding the relationship between ICT deployment and poverty alleviation in developing countries. It assess the digital technologies contribution to poverty reduction, through different channels of impact, like education, labor market, income and ICTtrade related activities. Using the sample of 40 developing countries between 1990 and 2019, it relies on macro data extracted from the World Bank Development...
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Simulation of the number of storm overflows considering changes in precipitation dynamics and the urbanisation of the catchment area: a probabilistic approach
PublikacjaThis paper presents a probabilistic methodology that allows the study of the interactions between changes in rainfall dynamics and impervious areas in urban catchment on a long- and short-term basis. The proposed probabilistic model predict future storm overflows while taking into account the dynamics of changes in impervious areas and rainfall. In this model, a logistic regression method was used to simulate overflow resulting...
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Determinants of Business Growth Aspirations among Polish Students: An Empirical Analysis
PublikacjaThis paper aims to discuss the concept of growth aspirations and growth intentions, as well as to identify factors that influence growth aspirations expressed by students with regard to their future businesses. On the basis of a literature review potential determinants of growth aspirations have been identified and tested empirically using data obtained from 223 students from the Pomeranian region in Poland. The authors...
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Soft Sensor Application in Identification of the Activated Sludge Bulking Considering the Technological and Economical Aspects of Smart Systems Functioning
PublikacjaThe paper presented the methodology for the construction of a soft sensor used for activated sludge bulking identification. Devising such solutions fits within the current trends and development of a smart system and infrastructure within smart cities. In order to optimize the selection of the data-mining method depending on the data collected within a wastewater treatment plant (WWTP), a number of methods were considered, including:...
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Comparison of low-temperature cracks intensity on pavements with high modulus asphalt concrete and conventional asphalt concrete bases
PublikacjaHigh modulus asphalt concrete (HMAC) base courses provide very good resistance to rutting and fatigue but they can increase the risk of low-temperature cracking as compared with conventional asphalt concrete (AC). The article presents the comparison of these two road materials in terms of low-temperature cracking. The statistical method based on the ordered logistic regression model was used. The analysis was based on results of...
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Efficiency of Artificial Intelligence Methods for Hearing Loss Type Classification: an Evaluation
PublikacjaThe evaluation of hearing loss is primarily conducted by pure tone audiometry testing, which is often regarded as golden standard for assessing auditory function. If the presence of hearing loss is determined, it is possible to differentiate between three types of hearing loss: sensorineural, conductive, and mixed. This study presents a comprehensive comparison of a variety of AI classification models, performed on 4007 pure tone...
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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublikacjaComputational cost is an important consideration for memory encoding prediction models that use data from dozens of implanted electrodes. We propose a method to reduce computational expense by selecting a subset of all the electrodes to build the prediction model. The electrodes were selected based on their likelihood of measuring brain activity useful for predicting memory encoding better than chance (in terms of AUC). A logistic...
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Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublikacjaCatheter-induced dissections (CID) of coronary arteries and/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated. We identified...
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Approval of an Arrangement in the Restructuring Proceedings and the Financial Condition of Companies Listed on the Stock Exchanges in Warsaw. Is There Any Relationship?
PublikacjaThis paper attempts to identify the financial indicators differentiating companies that are insolvent or at risk of insolvency and have successfully entered into an arrangement with their creditors from those that have not. In addition, a two-factor model for predicting the odds of an arrangement has been proposed. The research was conducted using a population of companies listed on stock exchanges in Warsaw that initiated restructuring...
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Age, frequency of volunteering, and Present-Hedonistic time perspective predict donating items to people in need, but not money to combat COVID-19 during lock-down
PublikacjaRestrictions due to COVID-19 necessitated staying at home, but in some cases, encouraged charitable behavior, e.g., donating items to people in need (e.g., clothes, food), or money to support combatting COVID-19. Drawing on the previous findings regarding helping during disastrous situations and roles of time perspective in helping behaviors, the study tested the predictive value of age, gender, previous volunteering, altruistic...
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Differential expression profile between amygdala and blood during chronic lithium treatment in a rat model of depression – a pilot study
PublikacjaLithium is a mood stabilizer widely used in the pharmacotherapy of bipolar disorder and treatment‑resistant depression. Taking into account dysregulated inflammatory activity in depression and the immunomodulatory role of lithium, we hypothesized that genes associated with inflammatory responses may be potential biomarkers of lithium action. We aimed to compare gene expression changes between the brain and the periphery after...
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News that Moves the Market: DSEX-News Dataset for Forecasting DSE Using BERT
PublikacjaStock market is a complex and dynamic industry that has always presented challenges for stakeholders and investors due to its unpredictable nature. This unpredictability motivates the need for more accurate prediction models. Traditional prediction models have limitations in handling the dynamic nature of the stock market. Additionally, previous methods have used less relevant data, leading to suboptimal performance. This study...
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Dependent self-employed individuals: are they different from paid employees?
PublikacjaThis study focuses on dependent self-employment, which covers a situation where a person works for the same employer as a typical worker while on a self-employment contractual basis, i.e., without a traditional employment contract and without certain rights granted to "regular" employees. The research exploits the individual-level dataset of 35 European countries extracted from the 2017 edition of the European Labour Force Survey...
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Psychological and physical components in forming preferences on urban greenery management – The case of trees
PublikacjaPublic opinion is increasingly important in managing urban greenery. In this regard, this study demonstrates the importance of sociological (environmental worldviews), psychological (place attachment, perceived benefits of trees), and physical factors (type of building people live in, and urban greenery) in forming residents’ opinions on whether the municipality or landowners should decide about tree removal on private land. Logistic...
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Detecting type of hearing loss with different AI classification methods: a performance review
PublikacjaHearing is one of the most crucial senses for all humans. It allows people to hear and connect with the environment, the people they can meet and the knowledge they need to live their lives to the fullest. Hearing loss can have a detrimental impact on a person's quality of life in a variety of ways, ranging from fewer educational and job opportunities due to impaired communication to social withdrawal in severe situations. Early...
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Factors affecting the conclusion of an arrangement in restructuring proceedings: evidence from Poland
PublikacjaThe EU Restructuring Directive (2019/1023) requires Member States to provide a preventive restructuring framework for financially distressed entities that remain viable or are likely to readily restore economic viability. The first step to a successful restructuring is the approval of an arrangement between the debtor and creditors. The main research objective of the article is to identify factors affecting the conclusion of an...
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Driving forces of informal employment: An empirical study based on Polish enterprise data
PublikacjaObjective: The article aims to indicate the determinants of informal employment in registered enterprises using company-level evidence from Poland. Research Design & Methods: The survey conducted among Polish small and medium-sized (SME) enterprises in 2018 was used to find the driving forces of informal employment in Poland. The adequate sample comprised 952 representative surveys derived from the computer-assisted telephone...
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FACTORS AFFECTING THE CONCLUSION OF AN ARRANGEMENT IN RESTRUCTURING PROCEEDINGS: EVIDENCE FROM POLAND
PublikacjaThe EU Restructuring Directive (2019/1023) requires Member States to provide a preventive restructuring framework for financially distressed entities that remain viable or are likely to readily restore economic viability. The first step to a successful restructuring is the approval of an arrangement between the debtor and creditors. The main research objective of the article is to identify factors affecting the conclusion of an...
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Organisational Competence vs Transferability of Knowledge in Cluster Organisations and Technology Parks
PublikacjaPurpose. The main paper aims to evaluate the impact of organisational competence on knowledge and information flows within cluster organisations and technology parks, with particular emphasis on innovative content knowledge. The paper addresses the research question: “What set of competencies of cooperating companies allows access to information and knowledge in cluster and parks structures?" Methodology. The authors report their...
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An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublikacjaSentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO)...
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Effect of the integration into Global Value Chains on the employment contract in Central and Eastern European countries
PublikacjaResearch background: In the era of globalization, there is a need to address decent work deficits in Global Value Chains (GVCs). The forms of working conditions reveal a broad dispersion of contents. The literature review exposes hardly any Europe-focused research assessing the socioeconomic impact of global production links and going beyond their pure economic effects assessed in terms of employment, productivity or wages. Purpose...
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Improving platelet‐RNA‐based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification
PublikacjaLiquid biopsy demonstrates excellent potential in patient management by providing a minimally invasive and cost-effective approach to detecting and monitoring cancer, even at its early stages. Due to the complexity of liquid biopsy data, machine-learning techniques are increasingly gaining attention in sample analysis, especially for multidimensional data such as RNA expression profiles. Yet, there is no agreement in the community...
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The effect of impacted third molars on second molar external root resorption, a cross-sectional cone beam computed tomography study
PublikacjaBackground: Third molars have the highest prevalence of impaction in teeth and can cause pathological damage on the adjacent second molars. This study aims to evaluate the effects of factors related to impacted third molars on external root resorption (ERR) in adjacent second molars using cone-beam computed tomography (CBCT). Material and Methods: In CBCTs, the effect of impacted third molars on the root surface of adjacent second...
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Ripple oscillations in the left temporal neocortex are associated with impaired verbal episodic memory encoding
PublikacjaBACKGROUND: We sought to determine if ripple oscillations (80-120 Hz), detected in intracranial electroencephalogram (iEEG) recordings of patients with epilepsy, correlate with an enhancement or disruption of verbal episodic memory encoding. METHODS: We defined ripple and spike events in depth iEEG recordings during list learning in 107 patients with focal epilepsy. We used logistic regression models (LRMs) to investigate the...
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Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents
PublikacjaThe construction industry suffers from workplace accidents, including injuries and fatalities, which represent a significant economic and social burden for employers, workers, and society as a whole.The existing research on construction accidents heavily relies on expert evaluations,which often suffer from issues such as low efficiency, insufficient intelligence, and subjectivity.However, expert opinions provided in construction...
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Development and validation of a model that includes two ultrasound parameters and the plasma D-dimer level for predicting malignancy in adnexal masses: an observational study
PublikacjaBackground: Pre-operative discrimination of malignant from benign adnexal masses is crucial for planning additional imaging, preparation, surgery and postoperative care. This study aimed to define key ultrasound and clinical variables and develop a predictive model for calculating preoperative ovarian tumor malignancy risk in a gynecologic oncology referral center. We compared our model to a subjective ultrasound assessment (SUA)...