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2023 International Conference on IT and Industrial Technologies, ICIT 2023

作者： Zulfiqar, Muhammad Imran Abdullah, Irum Akram, Aasma Mehmood, Shahid Fareeha Ali, Asad Nanjing University of Science & Technology School of Computer Science & Engineering Nanjing China Lahore College for Women University Department of Computer Science Jhang Pakistan Lahore College for Women University Department of Software Engineering Lahore Pakistan Higher Education Department Department of Computer Science Punjab Faisalabad Pakistan Air University Department of Business Administration Multan Pakistan

ISBN: (纸本)9798350315974

The task of maze solving has a rich historical background and continues to hold great significance in the realms of Robotics and Artificial Intelligence. The recent advancements in robotics technology aim to develop self-driving robots capable of autonomous operation, with the goal of streamlining our daily tasks. This emphasizes the focus of most research endeavors on augmenting sensor capabilities and refining algorithms to create robots that are adaptable and *** this paper, we present a contemporary approach to robotics that centers on the creation of self-navigating autonomous robots proficient in maze-solving while avoiding obstacles. This innovative research distinguishes itself from conventional line-following robots that merely adhere to predetermined paths. Instead, our proposed methodology enables the robot to navigate the maze independently, optimizing its path effectively. To achieve this, the robot employed in our study incorporates an ultrasonic sensor and operates on an open-source platform featuring an ATmega328P-based microcontroller *** core of this research lies in the development of a decision-making algorithm, which can be stored within the robot's programmable microcontroller, enabling it to tackle maze-solving tasks. The implications of this research span various applications, such as material handling, warehouse management, pipeline inspection, and bomb disposal. Compared to conventional line-following robots, our method provides superior results in terms of precision, recall, F1-score, time required to solve mazes, and practicality. © 2023 IEEE.

关键词： Microcontrollers

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LLM-based Methodology for Expanding 3D Metadata in Point Cloud 27

LLM-based Methodology for Expanding 3D Metadata in Point Clo...

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27th International Conference on Advanced Communications Technology, ICACT 2025

作者： Kim, Geon-Woo Kim, Joo-Chang Department of AI Computer Science and Engineering Kyonggi University Suwon16227 Korea Republic of Contents Convergence Software Research Institute Kyonggi University Suwon16227 Korea Republic of

ISBN: (纸本)9791188428137

This paper proposes a method for expanding the metadata of three-dimensional point cloud data using Large Language Models (LLMs). Currently, point cloud data plays a crucial role in various fields such as autonomous driving and medical image reconstruction, necessitating the expansion of metadata for efficient processing. Traditionally, metadata construction has relied on manual input, which is prone to errors. In this study, we propose a method that utilizes LLMs, particularly the Llama 3.1 model, to extract the center points of each class in the point cloud data and expand the metadata by adding these center points to the annotation files. By using center points, computational costs are reduced, and the performance of segmentation and detection models based on this data is improved. Copyright 2025 Global IT Research Institute (GIRI). All rights reserved.

关键词： Data assimilation

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Artificial Intelligence Based Sentence Level Sentiment Analysis of COVID-19

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computer Systems science & engineering 2023年第10期47卷 791-807页

作者： Sundas Rukhsar Mazhar Javed Awan Usman Naseem Dilovan Asaad Zebari Mazin Abed Mohammed Marwan Ali Albahar Mohammed Thanoon Amena Mahmoud Department of Software Engineering University of Management and TechnologyLahore54770Pakistan School of Computer Science The University of SydneySydneyAustralia Department of Computer Science College of ScienceNawroz UniversityDuhok42001Kurdistan RegionIraq College of Computer Science and Information Technology University of AnbarAnbar31001Iraq Department of Computer Science Umm Al Qura UniversityMecca24211Saudi Arabia Computer Science Department Faculty of Computers and InformationKafrelsheikh UniversityKafrelsheikhEgypt

Web-blogging sites such as Twitter and Facebook are heavily influenced by emotions,sentiments,and data in the modern ***,a widely used microblogging site where individuals share their thoughts in the form of tweets,has become a major source for sentiment *** recent years,there has been a significant increase in demand for sentiment analysis to identify and classify opinions or expressions in text or *** or expressions of people about a particular topic,situation,person,or product can be identified from sentences and divided into three categories:positive for good,negative for bad,and neutral for mixed or confusing *** process of analyzing changes in sentiment and the combination of these categories is known as“sentiment analysis.”In this study,sentiment analysis was performed on a dataset of 90,000 tweets using both deep learning and machine learning *** deep learning-based model long-short-term memory(LSTM)performed better than machine learning *** short-term memory achieved 87%accuracy,and the support vector machine(SVM)classifier achieved slightly worse results than LSTM at 86%.The study also tested binary classes of positive and negative,where LSTM and SVM both achieved 90%accuracy.

关键词： COVID-19 artificial intelligence machine learning deep learning sentimental analysis support vector classifier

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Optimized digital watermarking: Harnessing the synergies of Schur matrix factorization, DCT, and DWT for superior image ownership proofing

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Multimedia Tools and Applications 2025年第18期84卷 19817-19852页

作者： Al-Aiash, Issa Alquran, Rabee AlJamal, Mahmoud Alsarhan, Ayoub Aljaidi, Mohammad Al-Fraihat, Dimah Department of Information Technology Faculty of Prince Al-Hussein Bin Abdallah II for Information Technology The Hashemite University Zarqa13133 Jordan Department of Computer Science Faculty of Information Technology Zarqa University Zarqa13110 Jordan Department of Software Engineering Faculty of Information Technology Isra University Amman11622 Jordan

The contemporary context of abundant digital dissemination inherently gives rise to the need for media protection and the clear identification of ownership rights. This paper responded to this nagging issue of unauthorized media capture by developing a new digital watermarking approach uniting the Discrete Wavelet Transform DWT, Discrete Cosine Transform DCT, and Schur matrix factorization. The proposed watermark, which was a positive vector uniformly distributed, presented a high degree of robustness to several adversarial operating conditions, including histogram equalization, salt and pepper noise, ripple impact, smoothing attack, and cropping. The obtained results reveal the effectiveness of our approach. The correlation coefficient between watermarked and original images remains exceptionally high at 0.999998, ensuring minimal visual distortion. Mean Squared Error (MSE) graphs for both high-frequency (HH) and low-frequency (LL) domains demonstrate negligible changes after attacks, confirming the watermark's robustness. Notably, the watermark extraction process remains successful even after histogram equalization, as indicated by significantly lower MSE compared to random vectors. Moreover, the average processing times for different attacks are promising;Histogram Equalization and Salt and Pepper attacks each took 0.3 s, Ripple Attack required 0.28 s, Smoothing Attack completed in 0.29 s, and the Cropping Attack took 0.6 s. The robustness of our approach appears against the salt and pepper attack, which historically presented a vulnerability when employing Schur matrix factorization in image watermarking, indicating the novelty of and this contribution to improving media ownership verification. By combining disparate transformation methodologies, this technique offers a promising avenue for reinforcing the integrity and authenticity of digital media, thereby strengthening the foundations of intellectual property rights in the digital domain. © The Author(s), und

关键词： Discrete wavelet transforms

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Machine Learning-based Multi-path Reliable and Energy-efficient Routing Protocol for Underwater Wireless Sensor Networks 20

Machine Learning-based Multi-path Reliable and Energy-effici...

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20th International Conference on Frontiers of Information Technology, FIT 2023

作者： Khan, Zahid Ullah Aman, Muhammad Rahman, Wazir Ur Khan, Faran Jamil, Tooba Hashim, Rifhat Harbin Engineering University College of Underwater Acoustic Engineering Harbin150001 China University of Science and Technology Bannu Department of Software Engineering Pakistan Barani Institute of Information and Technology Department of Computer Science Rawalpindi Pakistan

ISBN: (纸本)9798350395785

The research on applications for Underwater Wireless Sensor Networks (UWSNs) including the investigation of submerged resources, gathering oceanographic data, conducting operational surveillance, and prevention from natural disasters is rapidly increasing. Traditional wireless sensor networks (TWSNs) are distinct from UWSNs. Routing protocols of TWSNs are also distinct from UWSNs routing protocols in terms of energy efficiency. Most of routing protocols have been developed to extract data from the ocean floor to the surface of waters. There are many challenges for indigenous designing of an efficient routing protocol for UWSNs, such as, design of reliable path for forwarding communicating data packets, managing the movement of nodes, configuration of sensor nodes, removing void communicating nodes and increasing the power efficiency of the system. This research focuses on designing a novel Machine learning-based multi-path reliable and energy-efficient routing protocol (M2RE2RP) for UWSNs. It will select an efficient path among the existing communication paths used by sensor nodes, which will ultimately increase the lifespan of the network. The simulation experiment results dictate that the proposed routing model M2RE2RP achieves better performance in terms of network throughput, end-to-end latency, total energy consumption and network lifetime. © 2023 IEEE.

关键词： Routing protocols

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Learning-Based MRI Response Predictions from OCT Microvascular Models to Replace Simulation-Based Frameworks 28th

Learning-Based MRI Response Predictions from OCT Microvascu...

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28th Annual Conference on Medical Image Understanding and Analysis, MIUA 2024

作者： Rustamov, Jaloliddin Rustamov, Zahiriddin Badawi, Nadia Lesage, Frederic Zaki, Nazar Damseh, Rafat Department of Computer Science and Software Engineering United Arab Emirates University Al Ain United Arab Emirates Biomedical Engineering Institute Ecole Polytechnique de Montreal MontrealQC Canada

ISBN: (纸本)9783031669545

Computational quantification of magnetic resonance imaging (MRI) response from neurovascular structures is used to investigate potential biomarkers for different types of cerebrovascular deteriorations at the microscopic scale. Simulation-based MRI requires fully resolved microvascular structures, with geometric and physiological parameters, from tissue volumes captured using microscopic imaging modalities, e.g., optical coherence tomography (OCT). The preparation of such input models hinders large cohort studies and requires extensive manual effort. Here, we propose using 3D neural networks as an alternative learning-based solution over MRI simulation schemes. We trained state-of-the-art 3D neural networks to predict the spin echo (SE) MRI response from OCT microvascular volumes. By validating against simulated signals, our result demonstrates that the 3D ResNet-based regression network achieves a high accuracy to predict MRI signals with an average mean square error (MSE) 2 of 82.8% and explained variance score of 82.9%. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Forecasting

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Emotion-Aware Music Recommendations: A Transfer Learning Approach Using Facial Expressions 1

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5th International Conference on Data and Information sciences, ICDIS 2023

作者： Annam, Sai Teja Bodapati, Jyostna Devi Konda, RajaSekhar Department of Advanced Computer Science and Engineering VFSTR Deemed to Be University Vadlamudi522213 India Software Engineering Manager & IEEE Senior Member IEEE San FranciscoCA94536 United States

ISBN: (数字)9789819969067

ISBN: (纸本)9789819969050

The influence of music on mood and emotions has been widely studied, highlighting its potential for self-expression and personal delight. As technology continues to advance exponentially, manually selecting and analyzing music from the vast array of artists, songs, and listeners becomes impractical. In this study, we propose a system called the "emotion-aware music recommendations" that leverages real-time facial expressions to determine a person’s emotional state. Deep learning models are employed to accurately detect facial emotions, leveraging the principles of transfer learning. By combining the model’s output with the mapped songs from the dataset, a personalized playlist is created. The main objective of the study is to effectively classify user emotions into six distinct categories using pre-trained models. Experimental studies conducted on the proposed approach employ the RAF-ML benchmark facial expression dataset. The findings indicate that the model outperforms existing approaches, demonstrating its effectiveness in generating tailored music recommendations. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Emotion Recognition

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Designing a Code Obfuscation Scheme for software Protection

Designing a Code Obfuscation Scheme for Software Protection

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2024 International Conference on Electrical and computer engineering Researches, ICECER 2024

作者： Azeta, Ambrose A. Awal, Abdulganiyu Azeta, Joy I. Hamunyela, Suama L. Santos, Albano dos Namibia University of Science and Technology Department of Software Engineering Windhoek Namibia Covenant University Department of Computer Science and Information Sciences Ota Nigeria Covenant University Department of Biological Sciences Ota Nigeria Namibia University of Science and Technology Department of Informatics Windhoek Namibia

ISBN: (纸本)9798331539733

software piracy and intellectual property theft has brought about a financial decrease in revenue for the producers of software systems. Moreso, malicious end-users act as Man-At-The-End (MATE) attackers and dangerously inspect software codes either statically or dynamically to steal them. Developers need to create client applications that contain confidential information and data. As a result, large scale software firms constantly strive to secure hidden algorithms and vital programming components contained in their applications in order to have competitive advantage. The focus of this study is to design a code obfuscation scheme for software and intellectual property protection. The methodology employed includes use of programming tool and algorithms that described the key processes of the scheme. To demonstrate the strength and capability of our approach, user evaluation was conducted to arrive at the cost, potency and resilience of the scheme. Results indicate that majority of the respondents believe that the developed obfuscator is inexpensive and that it does not adversely affect memory and execution time. The current study would provide software developers the tool to obscure their intellectual property against theft. © 2024 IEEE.

关键词： Attackers intellectual property obfuscation scheme software protection

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Cyber Security Threats on Multifunctional Devices and Mitigation Techniques 2

Cyber Security Threats on Multifunctional Devices and Mitiga...

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2nd International Conference on Business Analytics for Technology and Security, ICBATS 2023

作者： Al-Dmour, Nidal A. Farooq, Umer Sarwar, Irfan Iqbal, Muhammad Waseem Aqeel, Muhammad Khan, Wasim Ahmad Al Hamadi, Hussam Mutah University College of Engineering Department of Computer Engineering Jordan LGU Department of Computer Science Lahore Pakistan Superior University Department of Computer Science Lahore54000 Pakistan Superior University Department of Software Engineering Lahore54000 Pakistan NCBA&E Lahore School of Computer Science Pakistan Applied Science Research Center Applied Science Private University Amman11937 Jordan University of Dubai College of Engineering and IT PO Box 14143 United Arab Emirates

ISBN: (纸本)9798350335644

The risks discussed in this document are related to smart printers/ fax/ photocopiers/ or e-mail-enabled smart devices, also known as "document centers,". These devices can be purchased outright or rented every month. When an item reaches its end of life, it is either donated to a non-profit organization or returned to the manufacturer (OEM) or supplier at the end of a lease arrangement. These network-interconnected devices have an inherent susceptibility that most IT operations teams or information security professionals are unaware of. This effort will raise awareness of the dangers of losing a company's data. This discussion will focus on reported vulnerabilities, previous discussions, and given the author's view on the potential danger. Create instructions for potential users on how to use and disassemble these devices safely to prevent losing sensitive data. Lastly, the technological structure of two potential attack vectors against a document center of an organization will be demonstrated in this study. The study was conducted in government as well as the private sector, medium-sized enterprises (300 employees of each entity) settings, outside of normal business hours, with special authorizations and engagement, limiting the scope to a minimal set of devices. © 2023 IEEE.

关键词： Sensitive data

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On designing an unaided authentication service with threat detection and leakage control for defeating opportunistic adversaries

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Frontiers of computer science 2021年第2期15卷 161-179页

作者： Nilesh CHAKRABORTY Samrat MONDAL College of Computer Science and Software Engineering Shenzhen UniversityShenzhen518060China Department of Computer Science Indian Institute of Technology PatnaBihar801106India

Unaided authentication services provide the flexibility to login without being dependent on any additional *** power of recording attack resilient unaided authentication services(RARUAS)is undeniable as,in some aspects,they are even capable of offering better security than the biometric based authentication ***,high login complexity of these RARUAS makes them far from usable in *** adopted information leakage control strategies have often been identified as the primary cause behind such high login *** recent proposals have made some significant efforts in designing a usable RARUAS by reducing its login complexity,most of them have failed to achieve the desired usability *** this paper,we have introduced a new notion of controlling the information leakage *** maintaining a good security standard,the introduced idea helps to reduce the login complexity of our proposed mechanism—named as Textual-Graphical Password-based Mechanism or TGPM,by a significant *** with resisting the recording attack,TGPM also achieves a remarkable property of threat *** the best of our knowledge,TGPM is the first RARUAS,which can both prevent and detect the activities of the opportunistic recording attackers who can record the complete login activity of a genuine user for a few login *** study reveals that TGPM assures much higher session resiliency compared to the existing authentication services,having the same or even higher login ***,TGPM stores the password information in a distributed way and thus restricts the adversaries to learn the complete secret from a single compromised server.A thorough theoretical analysis has been performed to prove the strength of our proposal from both the security and usability *** have also conducted an experimental study to support the theoretical argument made on the usability standard of TGPM.

关键词： authentication recording attack premature attack opportunistic adversary leakage control threat prevention threat detection

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