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Healthcare Data Analytics Based on Machine Learning

Healthcare Data Analytics Based on Machine Learning

引用

2024 IEEE International Conference on Communications, Computing, Cybersecurity and Informatics, CCCI 2024

作者： Gancheva, Veska Technical University of Sofia Faculty of Computer Systems and Technologies Department of Programming and Computer Technologies Sofia1000 Bulgaria

ISBN: (纸本)9798350349832

Technology advancements have transformed medical science and practice, leading to the vast gathering of a wide range of medical data. Medical researchers use artificial intelligence techniques extensively because they enable the identification and creation of models of complicated datasets and the interactions between them. This, in turn, enables the successful prediction of future outcomes associated with a specific sickness type. An artificial intelligence-based approach to healthcare data analytics is presented, which leverages data to build a desired model and solve a particular issue. The suggested approach for healthcare data analytics uses a random forest and feedforward artificial neural network with two hidden layers as its basis to get the best model. © 2024 IEEE.

关键词： Adversarial machine learning

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Towards LLM-Based System Migration in Language-Driven Engineering 8th

Towards LLM-Based System Migration in Language-Driven Engin...

引用

8th International Conference on Engineering of computer-Based systems, ECBS 2023

作者： Busch, Daniel Bainczyk, Alexander Steffen, Bernhard Department of Computer Science Chair for Programming Systems TU Dortmund University Dortmund44227 Germany

ISBN: (纸本)9783031492518

In this paper we show how our approach of extending Language Driven Engineering (LDE) with natural language-based code generation supports system migration: The characteristic decomposition of LDE into tasks that are solved with dedicated domain-specific languages divides the migration tasks into portions adequate to apply LLM-based code generation. We illustrate this effect by migrating a low-code/no-code generator for point-and-click adventures from JavaScript to TypeScript in a way that maintains an important property: generated web applications can automatically be validated via automata learning and model analysis by design. In particular, this allows to easily test the correctness of migration by learning the difference automaton for the generated products of the source and the target system of the migration. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Verification

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ChatGPT in the Loop: A Natural Language Extension for Domain-Specific Modeling Languages 1st

ChatGPT in the Loop: A Natural Language Extension for Dom...

引用

1st International Conference on Bridging the Gap between AI and Reality, AISoLA 2023

作者： Busch, Daniel Nolte, Gerrit Bainczyk, Alexander Steffen, Bernhard Department of Computer Science Chair for Programming Systems TU Dortmund University Dortmund44227 Germany

ISBN: (纸本)9783031460012

This paper presents an approach to no-code development based on the interplay of formally defined (graphical) Domain-Specific Languages and informal, intuitive Natural Language which is enriched with contextual information to enable referencing of formally defined entities. The paper focuses on the use and automated integration of these enriched intuitive languages via ChatGPT-based code generation to exploit the best of both language paradigms for domain-specific application development. To compensate for the lack of control over the intuitive languages we apply automated system-level validation via automata learning and subsequent model checking. All this is illustrated using the development of point-and-click adventures as a minimal viable example. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Automata Learning Language-driven Engineering Large Language Models Low-Code/No-Code Prompt Engineering Software Engineering Verification Web Application

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Human VS AI-Generated Content: Where to Draw the Line? 33

Human VS AI-Generated Content: Where to Draw the Line?

引用

33rd International Scientific Conference Electronics, ET 2024

作者： Minkovska, Daniela V. Antonova, Elena V. Technical University of Sofia Faculty of Computer Systems and Technologies Department of Programming and Computer Technologies 8 Kliment Ohridski blvd. Sofia1000 Bulgaria

ISBN: (纸本)9798350376449

The integration and detection of AI (Artificial Intelligence) in a variety of fields, primarily education, are examined in this paper. With an emphasis on virtual assistants and their uses, it explores the potential and constraints of such technology. A study was conducted with students at the Technical University of Sofia, to assess their ability to distinguish between texts written by humans and AI. The results showcase that learners need to develop their critical analysis skills evidenced by their mixed expertise. © 2024 IEEE.

关键词： Adversarial machine learning

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Software Anomaly Detection Method Based on Artificial Neural Network 20

Software Anomaly Detection Method Based on Artificial Neural...

引用

20th IEEE International Conference on e-Business Engineering, ICEBE 2024

作者： Gancheva, Veska Technical University of Sofia Faculty of Computer Systems and Technologies Department of Programming and Computer Technologies 8 Kliment Ohridski blvd. Sofia1000 Bulgaria

ISBN: (纸本)9798350365856

A growing range of data sets have been created in recent years;these are used by platforms and software applications and kept in remote access repositories. Datasets are therefore more susceptible to harmful attacks. As a result, network security in data transmission is becoming a more important area of study. One well-known method for safeguarding computer systems is the deployment of intrusion detection systems. This study proposes an artificial intelligence based method for data analysis-based anomaly detection. Methods based on machine learning and rules are mixed together. The right rules are created via a genetic algorithm. Relevant features are extracted using principal component analysis with the goal of enhancing performance. The KDD Cup 1999 dataset is used to empirically validate the suggested procedure, satisfying the criterion of using appropriate data. Using the well-known benchmark dataset, the suggested approach is used to identify and examine four different kinds of attacks: Neptune, Ipsweep, Pod, and Teardrop. During the machine learning phase, the data is categorized into categories of attacks and normal behavior after the features set during the training phase are tested. For the purpose of data analysis, the input data is divided into training and testing sets for an artificial neural network. The first 80% of the data are used to train the neural network, and the remaining 20% are used for testing. The estimated accuracy improves with the number of epochs and is higher for training data and lower for validation test data, according to experimental results. Consequently, the trained model can be retained and used to detect discrepancies. The learnt model is used to the system to compute new input parameters that are not used during training or validation. © 2024 IEEE.

关键词： Network intrusion

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An Approach to Investigating Plagiarism in Artificial Intelligence Content 12

An Approach to Investigating Plagiarism in Artificial Intell...

引用

12th International Scientific Conference on computer Science, COMSCI 2024

作者： Minkovska, Daniela Veleva Antonova, Elena Ventseslavova Koparanov, Kiril Andreev Nakov, Plamen Ognyanov Technical University of Sofia Faculty of Computer Systems and Technologies Department of Programming and Computer Technologies 8 Kliment Ohridski blvd. Sofia1000 Bulgaria Technical University of Sofia Faculty of Computer Systems and Technologies Department of Computer Systems 8 Kliment Ohridski blvd. Sofia1000 Bulgaria

ISBN: (纸本)9798350392166

A growing number of human-centric tasks like learning, planning, and creative writing require the integration of Artificial Intelligence (AI) in the current era of exponential advancements. Such systems collect and analyze data on their own making the best use of available resources and providing creative solutions for challenging issues. The impact of AI on productivity, data analysis, flexibility, and real-time decision- making in a variety of fields is examined in this paper. Focusing on academic settings, the paper considers ethical concerns surrounding AI-generated content. According to a survey, even though many students use ChatGPT for writing and research, worries about academic integrity and plagiarism still exist. © 2024 IEEE.

关键词： Contrastive Learning

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Analysis of Trade-Offs Between Accuracy And Speed of Real-Time Object Detectors for the Tasks of Explosive Ordnance Detection 5

Analysis of Trade-Offs Between Accuracy And Speed of Real-Ti...

引用

5th IEEE KhPI Week on Advanced Technology, KhPIWeek 2024

作者： Mishchuk, Vadym Podorozhniak, Andrii Department of Computer Systems Networks and Cybersecurity National Aerospace University "Kharkiv Aviation Institute" Kharkiv Ukraine Department of Computer Engineering and Programming National Technical University "Kharkiv Polytechnic Institute" Kharkiv Ukraine

ISBN: (纸本)9798350384499

This paper investigates the performance trade-offs between accuracy and inference time in real-time object detection models, particularly for detecting landmines and unexploded ordnance (UXO). Using subsets from the COCO validation dataset, the models' performance is evaluated across various input resolutions. Object detection has seen substantial advancements over the past few decades, propelled by deep learning and enhanced computational resources. However, the balance between accuracy and inference time differs among models and configurations, requiring detailed evaluation to identify the optimal solution for specific applications like landmine and UXO detection. This balance is critical for autonomous robotic systems, where swift and accurate decision-making is imperative. ©2024 IEEE.

关键词： Landmine detection

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Understanding Student Success Prediction Using SHapley Additive exPlanations 11

Understanding Student Success Prediction Using SHapley Addit...

引用

11th International Scientific Conference on computer Science, COMSCI 2023

作者： Ujkani, Berat Minkovska, Daniela Nakov, Ognyan Technical University of Sofia Faculty of Computer Systems and Technologies Department of Programming and Computer Technologies 8 Kliment Ohridski blvd. Sofia1000 Bulgaria

ISBN: (纸本)9798350325256

Predicting student success is an important task in educational institutions, as it allows for targeted interventions and support systems to enhance educational outcomes. This paper explores the use of SHAP (SHapley Additive exPlanations) model-agnostic method in understanding and interpreting student success prediction. The predictive model was built using Multi-Layer Perceptron neural network algorithm on a large public dataset. By shedding light on the underlying factors driving student success, this research contributes to the advancement of data-driven decision-making in education. © 2023 IEEE.

关键词： Additives

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Development and Analysis of Genetic Algorithm for Optimization of Continuous Cast Billets Warehousing Process

Development and Analysis of Genetic Algorithm for Optimizati...

引用

2024 International Russian Smart Industry Conference, SmartIndustryCon 2024

作者： Shchegolikhin, Ivan S. Andreev, Sergey M. Nosov Magnitogorsk State Technical University Department of Computer Engineering and Programming Magnitogorsk Russia Nosov Magnitogorsk State Technical University Department of Automated Control Systems Magnitogorsk Russia

ISBN: (纸本)9798350395044

Warehouses are an important logistic component of various companies. Warehouses may have different layouts, equipment and their own features. Optimization of warehouse operations can decrease overhead costs and increase the economic efficiency of industry. The technological process of steel sheet production at a metallurgical company includes two major stages: casting of liquid steel into billets and rolling of these billets on a rolling mill. In order to coordinate the productivity of these two stages and to be able to fulfill orders promptly, a warehouse of slabs (billets) is used. Billets of different parties and steel grades are stored in stacks. The billets are moved to the warehouse for storage and from the warehouse to the rolling mill by bridge cranes. In this paper the problem of optimization of the process of continuous cast billets storage is solved to minimize the number of slab handling operations. The problem is decomposed into two subproblems SLAP (Storage Location Assignment Problem) and CSP (Crane Scheduling Problem). A modified genetic algorithm was applied to solve the problem. Using a simulation model of the warehouse, the efficiency of the algorithm was evaluated using different approaches to take the restrictions imposed on the process of slab handling into account. It is shown that the most effective is the algorithm in which there is no restriction on the placement of stacks of billets belonging to one melting. © 2024 IEEE.

关键词： Genetic algorithms

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Creating a Forecasting Model of Passenger Flows in Non-Scheduled Air Transportation 3

Creating a Forecasting Model of Passenger Flows in Non-Sched...

引用

3rd International Conference on Problems of Logistics, Management and Operation in the East-West Transport Corridor, PLMO 2024

作者： Aghayev, Nadir Nazarli, Dashqin National Aviation Academy of the Republic of Azerbaijan Department of Computer Systems and Programming Baku Azerbaijan National Aviation Academy of the Republic of Azerbaijan Department of Air Transport Production Baku Azerbaijan

ISBN: (纸本)9798350353099

In the article, a new method of building a forecast model using a fuzzy approach for charter air transportation time series with intra-series multiplicative changes is proposed. The method is based on the use of correlation functions in the calculation of forecast values based on statistical indicators of intra-row changes. In regular air transportation, the changes in the time series of statistical indicators are stable. On charter flights, these changes are unstable. This is due to the strong random effects of external factors (a sudden increase in demand for flights, economic changes, etc.) on the formation of charter flights. For this reason, the application of models based on trend changes does not give good enough results when building forecast models for charter flights. Therefore, to solve the problem, we propose to build a forecast model using a fuzzy approach, using the randomness of the intra-series changes of the statistical indicators of this type of air transportation. The researched method was checked based on the actual data of the time series of charter flights, and the results were obtained within acceptable limits. © 2024 IEEE.

关键词： charter flights forecasting fuzzy approach non-scheduled air transportation optimal model time series

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