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3rd International Conference on Applied Artificial Intelligence and computing, ICAAIC 2024

作者： Milanovic, Aleksandar Jovanovic, Luka Zivkovic, Miodrag Bacanin, Nebojsa Cajic, Miroslav Antonijevic, Milos Singidunum University Department of Informatics and Computing Beograd Serbia Singidunum University Faculty of Technical Sciences Beograd Serbia University 'Union Nikola Tesla' Faculty of Information Technology and Engineering Cara Dusana Beograd Serbia

ISBN: (纸本)9798350375190

Workplace safety is crucial across all industries, particularly in dynamic environments like construction and road infrastructure. The application of computer vision holds promise in enhancing safety measures by automatically detecting hazards and identifying risks in real-time. Despite its potential, computer vision's role in workplace safety remains under-explored. This study investigates the effectiveness of three pre-trained versions of the YOLOv8 model in detecting reflective vests, a critical safety element, using real-world data. The YOLOv8 model offers fast and accurate recognition, enabling efficient monitoring of work activities and timely alerts for safety breaches. Results demonstrate the model's capability in improving workplace safety while maintaining manageable computational demands. This research underscores the significance of leveraging advanced technological solutions like CV to mitigate risks and ensure the well-being of employees in hazardous work environments. © 2024 IEEE.

关键词： Accident prevention

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Automated Classification and Segmentation of Brain Tumor Images using Backboned ResUNet Framework 6

Automated Classification and Segmentation of Brain Tumor Ima...

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6th International Conference on Mobile computing and Sustainable Informatics, ICMCSI 2025

作者： Prasanalakshmi, B. Anitha, Cuddapah Balamanigandan, R. Mahaveerakannan, R. Gade, N.V. Ratnakishor Adjunct Faculty Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Tamil Nadu Chennai India Department of Computer Science and Engineering School of Computing Mohan Babu University Andhra Pradesh Tirupati India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Tamil Nadu Chennai India

ISBN: (纸本)9798331522667

One of the most challenging issues in computer imaging is the automated segmentation of brain tumors using Magnetic Resonance Images (MRI). Several approaches are explored using Deep Neural Networks in image segmentation since they perform well in automated tumor segmentation using tumor scans. Due to the complexity, training deeper neural networks usually takes a long time and many processing resources. An automated approach for classifying and segmenting images of Brain tumor MRI is proposed. As a hybrid transfer learning approach, modified ResNet50 identifies the class of MRI images as Benign or malignant. After identifying the Benign images, the tumor’s location is segmented using a hybrid network involving ResUNet with the Xception network as Backbone. This combination approach is chosen after its comparative analysis with other backbones. Various combination approaches are carried out, and performance metrics like Jaccard, Dice, and Tversky coefficient are done to prove the ResUNet backboned with Xception plays a better role concerning accuracy and speed. The proposed approach was tested on the dataset Cancer Imaging Archive to validate its efficiency. The proposed model has an average dice similarity coefficient score of 0.94, outperforming the conventional transfer learning training method with all the layers. © 2025 IEEE.

关键词： Magnetic resonance imaging

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Precision Forecasting of Stock Prices: Leveraging XGBoost and technical Indicator for Advanced Predictive Modeling 1

Precision Forecasting of Stock Prices: Leveraging XGBoost an...

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1st International Conference on Intelligent Systems and Computational Networks, ICISCN 2025

作者： Yuvaraj, S. Chenni Kumaran, J. Vinston Raja, R. Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Chennai India Srm Institute of Science and Technology Faculty of Engineering and Technology School of Computing Department of Computational Intelligence Kattankulathur Chennai India

ISBN: (数字)9798331529246

ISBN: (纸本)9798331529246

The investigation aims to evaluate the performance of machine learning techniques, particularly the XGBoost regression method, for stock price prediction with the help of technical indicators. The research targets the adjusted closing price to reduce the autocorrelation problem in time series. The Five Days and Ten Days Exponential Moving Averages (EMA-5 and EMA-10) are involved in refining feature selection. The performance of the model was evaluated using different error metrics, namely, Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Coefficient of Determination (R2). The results indicate that the XGBoost model, combined with EMA-5 and EMA-10, achieves high predictive performance, obtaining an r2 value of 0.98. It implies that incorporating short-term EMAs into advanced machine learning techniques drastically improves stock price forecasting. © 2025 IEEE.

关键词： Time series

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Evaluation of Ethernet Subsystem for Domain controller in Autonomous Vehicles

Evaluation of Ethernet Subsystem for Domain Controller in Au...

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2021 Zooming Innovation in Consumer Technologies Conference, ZINC 2021

作者： Kenjic, Dusan Antic, Marija Bjelica, Milan University of Novi Sad Faculty of Technical Sciences Department of Computing and Control Engineering Serbia

ISBN: (纸本)9781665404174

The expansion of the automotive industry is reflected in the expansion of functionalities and services offered by a modern vehicle. In order for all of them to be executed, it is also necessary to increase the number of physical components within the vehicle. As the entire system grows, so does the problem of connecting the entities within it. The efficient simplification of the system is achieved by introducing domain controllers, and separating the physical components based on the functionality they perform, while creating the backbone communication network between domain controllers. Time-critical and other performance requirements, which are driven by the development of autonomous driving, demand the utilization of new standards and solutions for this communication network backbone. One of those solutions is Automotive Ethernet. In this paper, an implementation of the Ethernet subsystem of the domain controller for autonomous vehicles will be presented and evaluated. © 2021 IEEE.

关键词： Automotive industry

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Relation Based Knowledge Extraction for Animal Farm Management 12

Relation Based Knowledge Extraction for Animal Farm Manageme...

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12th IEEE International Conference on Intelligent Systems, IS 2024

作者： Vatchova, Boriana Boneva, Yordanka Gegov, Alexander Institute of Information and Communication Technologies Bulgarian Academy of Sciences Sofia Bulgaria School of Computing University of Portsmouth Portsmouth United Kingdom Technical University of Sofia English Faculty of Engineering Sofia Bulgaria

ISBN: (纸本)9798350350982

This paper presents an application of a knowledge extraction method developed by the authors to animal farm management. The main purpose of the paper is to process information on the relationships between profits and costs in livestock farming. The paper uses expert knowledge as a benchmark approach for knowledge extraction and a fuzzy method for comparative validation. The academic novelty in the paper is the first-time application of the relation based knowledge extraction method to livestock farming. © 2024 IEEE.

关键词： expert knowledge fuzzy sets information processing knowledge extraction livestock farming relations

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Bitroute SOME/IP: Implementation of a Scalable and Service Oriented Communication Middleware 45

Bitroute SOME/IP: Implementation of a Scalable and Service O...

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45th Jubilee International Convention on Information, Communication and Electronic Technology, MIPRO 2022

作者： Vujanic, M. Trifunovic, N. Kastelan, I. Kovacevic, B. University of Novi Sad Faculty of Technical Sciences Department of Computing and Control Engineering Serbia RT-RK Institute for Computer Based Systems Novi Sad Serbia

ISBN: (纸本)9789532331035

SOME/IP is a communication protocol introduced in automotive industry to enable Service Oriented Architecture which is not possible using traditional automotive protocols such as CAN or FlexRay. A trend emerging in the last years in the Advanced Driver Assistance Systems (ADAS) is that SOME/IP became one of main communication protocols used for communication between safety and performance ECU devices. Currently in the market, including the open-source solutions, there is a set of different SOME/IP implementations that have different audience and combination of characteristics like high royalty costs, available feature set and software solution maturity. This paper presents the Bitroute SOME/IP, a new implementation of the SOME/IP communication protocol with focus on performance and deployment platform independency and compares it with the open-source solution from The Connected Vehicle Systems Alliance (COVESA). © 2022 Croatian Society MIPRO.

关键词： Automotive industry

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An approach towards Model-To-Model Mapping between AUTOSAR and Android systems 45

An approach towards Model-To-Model Mapping between AUTOSAR a...

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45th Jubilee International Convention on Information, Communication and Electronic Technology, MIPRO 2022

作者： Zlatkovic, Radomir Cabrilo, Vuk Antic, Marija Kovacevic, Branimir University of Novi Sad Faculty of Technical Sciences Department of Computing and Control Engineering Serbia RT-RK Institute for Computer Based Systems Novi Sad Serbia

ISBN: (纸本)9789532331035

Every new generation of modern vehicles aims to provide the customers with a higher level of comfort and entertainment services. Consequently, the burden is placed upon the manufacturers to incorporate ever more complex electronic systems in their products and introduce service-based technologies. To meet these demands, service-oriented architecture (SOA) has become an integral part of the Adaptive AUTOSAR as the industry standard. Also, mobile services and applications are natively supported in the new in-vehicle infotainment systems (IVI) which usually run on the Android operating system. As these fundamentally different technologies are incorporated in the vehicles, the developers are facing the challenge of connecting them and exchanging information between the services running in different domains. Service-oriented architectures usually rely on a model-driven engineering approach to facilitate the development of the applications. However, as the complexity of the system grows, the mapping of various metamodels becomes a challenge, as no single standard is used across all domains in the vehicle. This paper provides a possible solution for mapping the already existing AUTOSAR metamodel to an Android Interface Definition Language (AIDL) metamodel. By applying the proposed mapping, it is possible to build applications that require the cooperation of various domains within the vehicle. © 2022 Croatian Society MIPRO.

关键词： Mapping

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Accidental Centralization: Pitfalls of Blockchain-Based Project Architectures

Accidental Centralization: Pitfalls of Blockchain-Based Proj...

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Electrical, Electronic and computing engineering (IcETRAN), International Conference on

作者： Veljko B. Petrović Dinu Dragan Dušan B. Gajlć Control and Computing Department Faculty of Technical Sciences University of Novi Sad Novi Sad Serbia

ISBN: (数字)9798350386998

ISBN: (纸本)9798350387001

Making use of blockchain in complex projects in ways which scale and keep costs down can lead to very complex architectural patterns. The problem with such patterns is that it is very easy to set up a system that only seems decentralized but, in fact, operates under a degraded trust model or is even centralized in practice. Using a blockchain to implement a centralized system represents a grotesque waste of computational resources for no benefit at all. This paper analyzes several cases of such architectural malfunction and shows how degraded trust can occur, how to detect it, and how to respond to this issue.

关键词： Privacy Costs Computational modeling Design methodology Computer architecture Trustless services Blockchains

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Face image authentication scheme based on MTCNN and SLT

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Multimedia Tools and Applications 2025年 1-43页

作者： Thabit, Rasha Al-Askari, Mohanad A. Mohammed, Dunya Zeki Anaam, Elham Abdulwahab Mahmood, Zainab H. Jabbar, Dina Jamal Salih, Zahraa Aqeel Information System Department College of Computer Sciences and Information Technology University of Al-Anbar Al-Anbar Iraq Computer Engineering Department College of Engineering Al-Iraqia University Baghdad Iraq Electronic and Communications Engineering Department College of Engineering Gilgamesh University Baghdad Iraq Faculty of Computing and Informatics Multimedia University Selangor Cyberjaya Malaysia Department of Cybersecurity Engineering College of Information Engineering Al-Nahrain University Baghdad Iraq Electrical Engineering Technical Collage Middle Technical University Baghdad Iraq Department of Business Administration Alamaal University College Baghdad Iraq

DeepFakes and face image manipulation methods have been widely distributed in the last few years and several techniques have been presented to check the authenticity of the face image and detect manipulation if exists. Most of the available manipulation detection techniques have been successfully applied to reveal one type of manipulation under specific conditions, however, many limitations and challenges can be encountered in this field. To overcome some limitations and challenges, this paper presents a new face image authentication (FIA) scheme based on Multi-Task Cascaded Conventional Neural Networks (MTCNN) and watermarking in Slantlet transform (SLT) domain. The proposed FIA scheme has three main algorithms that are face detection and selection, embedding, and extraction algorithms. Different block sizes have been used to divide the image into non-overlapping blocks followed by classifying them into two groups that are blocks from face area (FA) and blocks from the remaining area (RA) of the image. In the embedding algorithms, the authentication information is generated from FA blocks and embedded in the RA blocks. In the extraction algorithms, the embedded information is extracted from RA blocks and compared with the calculated data from FA blocks to reveal manipulations and localize the manipulated blocks if exist. Extensive experiments have been conducted to evaluate the performance of the proposed FIA scheme for different face images. The experimental work included tests for payload, capacity, visual quality, time complexity, and localization of manipulations. The results proved the efficiency of the proposed scheme in detecting and localizing different face image manipulations such as attributes attacks, retouching attacks, expression swap, face swap, and morphing attacks. The proposed scheme overcomes many limitations and it is 100% accurate in localizing the tampered blocks which makes it a better candidate for practical applications. © The Author(s), un

关键词： Authentication

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One solution of providing ADAS data to the IVI domain via the Android Java service

One solution of providing ADAS data to the IVI domain via th...

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Zooming Innovation in Consumer Electronics International Conference (ZINC)

作者： Dušan Stanišić Marija Antić Dušan Kenjić Luka Bilač Department of Computing and Control Engineering Faculty of Technical Sciences University of Novi Sad Novi Sad Serbia

In recent years, manufacturers are working parallel in developing and integrating two in-vehicle systems, an Advanced Driver Assistance System (ADAS) and In-Vehicle Infotainment (IVI). ADAS’s purpose is to increase safety and aid the driver while the vehicle is in motion, by using various sensors to perceive the vehicle surrounding or the driver’s errors and respond accordingly. Consumer applications in the IVI domain would significantly benefit from accessing such vehicle-specific data. Unfortunately, due to active vehicle system architecture requirements, the IVI domain cannot achieve communication with the ADAS by following traditional signal-oriented mechanisms. In addition, Android paved its way into the IVI domain as the most common Operating System because of its high flexibility and customization, but without being adapted for communication with ADAS. This paper offers a solution for enabling Android applications to access ADAS data via Java services. Data is procured over GENIVI company’s SOME/IP-based communication middleware, integrated within the services. Communication performance is measured, evaluated, and limitations are identified.

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