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Global adaptive histogram feature network for automatic segmentation of infection regions in CT images
Accurate and timely diagnosis of COVID-like virus is of paramount importance for lifesaving. In this work, deep learning techniques are applied to...
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Federated learning for digital healthcare: concepts, applications, frameworks, and challenges
Various hospitals have adopted digital technologies in the healthcare sector for various healthcare-related applications. Due to the effect of the...
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Why the use of domain-specific modeling in airworthy software requires new methods and how these might look like? (extended version)
The use of domain-specific modeling (DSM) in safety-critical avionics is rare, even though the ever-increasing complexity of avionics systems makes...
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Unveiling the impact of employee-customer familiarity on customer purchase intentions: an empirical investigation within the realm of web-based date analytics
This research delves into the intricate dynamics of employee-customer familiarity and its profound influence on customer purchase intentions within...
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Understanding the GDPR from a requirements engineering perspective—a systematic map** study on regulatory data protection requirements
Data protection compliance is critical from a requirements engineering (RE) perspective, both from a software development lifecycle (SDLC)...
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MIM: A multiple integration model for intrusion detection on imbalanced samples
The quantity of normal samples is commonly significantly greater than that of malicious samples, resulting in an imbalance in network security data....
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Signal processing implementation of low-cost target speed detection of CW radar using FPGA
The low-cost Continuous Wave (CW) radar architecture for object speed detection is presented in this research. An FPGA (Field-Programmable Gate...
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Survey-based analysis of cybersecurity awareness of Turkish seafarers
In recent years, vessels have become increasingly digitized, reflecting broader societal trends. As a result, maritime operations have become an...
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Smart contract vulnerabilities detection with bidirectional encoder representations from transformers and control flow graph
Up to now, the smart contract vulnerabilities detection methods based on sequence modal data and sequence models have been the most commonly used....
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A robust method for malware analysis using stacking classifiers and dendrogram visualization
Malware analysis is a vital and challenging task in the ever-changing cyber threat landscape. Traditional signature-based methods cannot keep up with...
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A principal label space transformation and ridge regression-based hybrid gorilla troops optimization and jellyfish search algorithm for multi-label classification
Classification as an essential part of Machine Learning and Data Mining has significant roles in engineering, medicine, agriculture, military, etc....
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iDOCEM
In the business process lifecycle, models can be approached from two perspectives: on the one hand, models are used to create systems in the design...
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Aggregating the response in time series lag models using quad weight kernel: impact of environmental factors on schizophrenia admissions
There has been a growing apprehension in the past few years concerning the issue of pollution and climate change. Several articles have shown the...
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Electromagnetic properties of coal using microstrip and an algorithm based on the Nicolson-Ross-Weir method
The work implements an experimental methodology to find the dielectric parameters: electrical permittivity, effective permittivity, magnetic...
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What you see is what you trace: a two-stage interview study on traceability practices and eye tracking potential
The benefits of traceability have widely been discussed in research. However, studies have also shown that traceability practices are still not...
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Requirements for modelling tools for teaching
Modelling is an important activity in software development and it is essential that students learn the relevant skills. Modelling relies on dedicated...
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Exploiting recurrent graph neural networks for suffix prediction in predictive monitoring
Predictive monitoring is a subfield of process mining that aims to predict how a running case will unfold in the future. One of its main challenges...
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Deep learning-based classification and application test of multiple crop leaf diseases using transfer learning and the attention mechanism
Crop diseases are among the major natural disasters in agricultural production that seriously restrict the growth and development of crops,...
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ASDMG: business topic clustering-based architecture smell detection for microservice granularity
Microservices architecture smells can significantly affect the quality of microservices due to poor design decisions, especially the granularity...
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A splash of color: a dual dive into the effects of EVO on decision-making with goal models
Recent approaches have investigated assisting users in making early trade-off decisions when the future evolution of project elements is uncertain....
