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DeciLS-PBO: an effective local search method for pseudo-Boolean optimization

Frontiers of computer Science 2024年第5期18卷 239-241页

作者： Luyu JIANG Dantong OUYANG Qi ZHANG Liming ZHANG College of Computer Science and Technology Jilin UniversityChangchun 130012China Key Laboratory of Symbolic Computation and Knowledge Engineering(Ministry of Education) Jilin UniversityChangchun 130012China

1 Introduction Local search method is a rising star for solving combinatorial optimization problems in recent years,and the state-of-the-art local search-based incomplete Maximum Satisfiability(MaxSAT)solversshowpromi... 详细信息

关键词： Max optimization local

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SmartSignQuiz A Colour-Based Interactive Quiz System for Hard to Talk and Hard to Hear Students 5

SmartSignQuiz A Colour-Based Interactive Quiz System for Har...

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5th International Conference on Sustainable Communication Networks and Application, ICSCNA 2024

作者： Subbulakshmi, N. Chandru, R. Ariffa Begum, S. Pavalla, Manju Vallabha Palagiri, Mohammed Muzammil Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Tamilnadu India Sri Ramakirshna Engineering College Department of Electronics and Communication Engineering Tamilnadu India

ISBN: (纸本)9798331530013

The growing field of artificial intelligence (AI) provides new opportunities to develop inclusive educational tools tailored to diverse student needs. This study introduces SmartSignQuiz, an innovative colour-based interactive quiz system for hard-to-talk and hard-to-hear students. The system combines facial recognition and colour detection technologies, facilitating real-time participation without relying on verbal communication. SmartSignQuiz ensures accurate student identification through a face recognition module while employing colour-coded responses for quiz interaction. The primary objective is to create an accessible, non-verbal learning platform that promotes active engagement for all students. The study evaluates the system's accuracy, computational efficiency, and impact on educational outcomes, demonstrating its potential to enhance inclusivity in classroom environments. © 2024 IEEE.

关键词： Colour Detection computer Vision Facial Recognition

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Intelligent Monitoring System for Automatic Air Conditioning System 5

Intelligent Monitoring System for Automatic Air Conditioning...

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5th International Conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2024

作者： Manikandan, P. Swedheetha, C. Ram Mohan, R.L. Kumar, Sandala Likith Reddy, Peram Damodar Sri Sai, Pachabotla Adithya Kalasalingam Academy of Research and Education Department of Electronics and Communication Engineering Krishnankoil India Velammal College of Engineering and Technology Department of Computer Science and Engineering Madurai India

ISBN: (纸本)9798331518097

In order to improve indoor air quality, optimize energy consumption and avoid the accidents due to gas leakage, this paper proposes an intelligent air conditioning system that integrates several sensors such as DHT11, PIR sensors, MG6 Gas sensor and PMS7003 sensor and control mechanisms. An Arduino Mega, the system's central component, synchronizes data from several sensors to efficiently control the air conditioner and other linked equipment. This system keeps track of how many people enter and leave the space, enabling the air conditioning system to modify its settings in real time according to occupancy. When the room is empty, this feature saves energy. If gas leakage is present, system notifies users through a buzzer and turn off the AC. Many users often forget to clean their AC filters regularly, which can lead to reduced efficiency, higher energy consumption, and poorer air quality. Our innovative AC system addresses this common issue. Once the dust level crosses a predefined threshold, the system triggers a clean filter alert, reminding to act before it affects performance. Also, the air conditioner kicks on to cool the room if the outside temperature is high and the inside temperature is higher than an acceptable level. In contrast, the air conditioner is shut off to avoid needless cooling if the inside temperature is low. A display unit shows temperature, humidity, occupancy, gas levels, and dust concentration. This integrated technique automatically modifies the system's operation based on conditions, ensuring not only a more hygienic and comfortable environment but also improved energy efficiency © 2024 IEEE.

关键词： Air quality

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Evaluating and Contrasting the Performance of Web Development Technologies 9

Evaluating and Contrasting the Performance of Web Developmen...

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9th International Conference on Communication and Electronics Systems, ICCES 2024

作者： Swedheetha, C. Shruthika, C. Preethi, Rubi Vedha Varshini, T.B.J. Maryam, Sabreen Manikandan, P. Velammal College of Engineering and Technology Department of Computer Science and Engineering Madurai India Kalasalingam Academy of Research and Education Department of Electronics and Communication Engineering Virudhunagar India

ISBN: (纸本)9798350377972

The next generation of webpages is heavily influenced by large scale, high concurrency, and massive amounts of data. Building data-intensive web apps has made *** popular and effective. We employed scenario testing and benchmark testing to examine and contrast the performance of ***, Python-Web, and PHP. Per the testing results, PHP and Python-Web handle a lot less requests in a given amount of time than ***, which is evident from some useful performance metrics. Our findings, taken together, show that *** is the most lightweight and efficient of the three, making it a good choice for I/O-intensive websites;PHP, on the other hand, is best suited for small- to medium-sized applications, while Python-Web is developer-friendly and excels at large web architectures. This research study includes the performance evaluation of web development technologies. © 2024 IEEE.

关键词： Python

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A level set model with shape prior constraint for intervertebral disc MRI image segmentation

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Multimedia Tools and Applications 2025年第9期84卷 6755-6783页

作者： Tian, Zhuangzhou Wang, Shengsheng College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China

Accurate intervertebral disc image segmentation is necessary for further treatment. However, existing methods are difficult to segment due to the intensity inhomogeneity of intervertebral disc MRI images and the similarity in intensity between the intervertebral disc and the surrounding regions. This paper proposes a novel level set model by introducing a shape prior constraint for automatic and accurate segmentation. We utilize a detection model and intensity change to obtain rectangle prior information, which is used to define a shape constraint term. Then, combining data and regularizing terms construct an energy function and employ the steepest descent method minimization to get segmentation results. Finally, we apply the proposed new method to segment intervertebral disc images and get promising results. Extensive experiments and comparisons show that our model is more efficient and accurate. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Image segmentation

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Enhancement of UAV Data Security and Privacy via Ethereum Blockchain Technology

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computers, Materials & Continua 2023年第8期76卷 1797-1815页

作者： Sur Singh Rawat Youseef Alotaibi Nitima Malsa Vimal Gupta Department of Computer Science and Engineering JSS Academy of Technical EducationNoida201301India Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia

Unmanned aerial vehicles(UAVs),or drones,have revolutionized a wide range of industries,including monitoring,agriculture,surveillance,and supply ***,their widespread use also poses significant challenges,such as public safety,privacy,and ***,targetingUAVs have become more frequent,which highlights the need for robust security *** technology,the foundation of cryptocurrencies has the potential to address these *** study suggests a platform that utilizes blockchain technology tomanage drone operations securely and *** incorporating blockchain technology,the proposed method aims to increase the security and privacy of drone *** suggested platform stores information on a public blockchain located on Ethereum and leverages the Ganache platform to ensure secure and private blockchain *** wallet for Ethbalance is necessary for BCT *** present research finding shows that the proposed approach’s efficiency and security features are superior to existing *** study contributes to the development of a secure and efficient system for managing drone operations that could have significant applications in various *** proposed platform’s security measures could mitigate privacy concerns,minimize cyber security risk,and enhance public safety,ultimately promoting the widespread adoption of *** results of the study demonstrate that the blockchain can ensure the fulfillment of core security needs such as authentication,privacy preservation,confidentiality,integrity,and access control.

关键词： Unmanned aerial vehicles(UAVs) blockchain data privacy network security smart contract Ethereum

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Interference Suppression and Jitter Elimination Ability-Based Adaption Tracking Guidance for Robotic Fishes

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 126-137页

作者： Dongfang Li Jie Huang Rob Law Xin Xu Limin Zhu Edmond Q.Wu IEEE the School of Electrical Engineering and Automation Fuzhou University the Key Laboratory of System Control and Information Processing Ministry of Education the School of Electrical Engineering and Automation Fuzhou University 5G+Industrial Internet Institute Fuzhou University the University of Macau the College of Mechatronics and Automation National University of Defense Technology the School of Mechanical Engineering Shanghai Jiao Tong University the Department of Computer Science and Engineering Shanghai Jiao Tong University

This work presents an adaptive tracking guidance method for robotic fishes. The scheme enables robots to suppress external interference and eliminate motion jitter. An adaptive integral surge line-of-sight guidance rule is designed to eliminate dynamics interference and sideslip issues. Limited-time yaw and surge speed observers are reported to fit disturbance variables in the model. The approximation values can compensate for the system's control input and improve the robots' tracking ***, this work develops a terminal sliding mode controller and third-order differential processor to determine the rotational torque and reduce the robots' run jitter. Then, Lyapunov's theory proves the uniform ultimate boundedness of the proposed method. Simulation and physical experiments confirm that the technology improves the tracking error convergence speed and stability of robotic fishes.

关键词： Adaptive integral surge line-of-sight approximation robotic fish speed observer

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Empirical mode decomposition of near-infrared spectroscopy signals for predicting oil content in palm fruits

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Information Processing in Agriculture 2023年第3期10卷 289-300页

作者： Inna Novianty Ringga Gilang Baskoro Muhammad Iqbal Nurulhaq Muhammad Achirul Nanda Computer Engineering Study Program College of Vocational StudiesIPB UniversityBogor 16680Indonesia Informatics Management Study Program College of Vocational StudiesIPB UniversityBogor 16680Indonesia Technology and Plantation Production Management Study Program College of Vocational StudiesIPB UniversityBogor 16680Indonesia Department of Agricultural and Biosystem Engineering Faculty of Agro-Industrial TechnologyUniversitas PadjadjaranJatinangor 45363Indonesia

Oil content estimation in palm fruits is a precious property that significantly impacts oil palm production,starting from the upstream and *** content can be used to monitor the progress of the oil palm fresh fruit bunch(FFB)and be applied to identify product *** on the near-infrared(NIR)signals,this study proposes an empirical mode decomposition(EMD)technique to decompose signals and predict the oil content of palm ***,350 palm fruits with Tenera varieties(Elaeis guineensis ***),at various ages of maturity,were harvested from the Cikabayan Oil Palm Plantation(IPB University,Indonesia).Second,each sample was sent directly to the laboratory for NIR signal measurements and oil content ***,the EMD analysis and arti-ficial neural network(ANN)were employed to correlate the NIR signals and oil ***,a robust EMD-ANN model is generated by optimizing the lowest possible *** on performance evaluation,the proposed technique can predict oil content with a coefficient of determination(R2)of 0.933±0.015 and a root mean squared error(RMSE)of 1.446±*** results demonstrate that the model has a good predictive capacity and has the potential to predict the oil content of palm fruits directly,without neither solvents nor reagents,which makes it environmentally ***,the proposed technique has a promising potential to be applied in the oil palm *** like this will lead to the effective and efficient management of oil palm production.

关键词： Artificial neural network Empirical mode decomposition Oil palm Oil content prediction

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Lightweight axiom pinpointing via replicated driver and customized SAT-solving

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Frontiers of computer Science 2023年第2期17卷 121-133页

作者： Dantong OUYANG Mengting LIAO Yuxin YE College of Computer Science and Technology Jilin UniversityChangchun 130012China Key Laboratory of Symbolic Computation and Knowledge Engineering(Jilin University) Ministry of EducationChangchun 130012China

In description logic,axiom pinpointing is used to explore defects in ontologies and identify hidden justifications for a logical *** recent years,SAT-based axiom pinpointing techniques,which rely on the enumeration of minimal unsatisfiable subsets(MUSes)of pinpointing formulas,have gained increasing *** with traditional Tableau-based reasoning approaches,SAT-based techniques are more competitive when computing justifications for consequences in large-scale lightweight description logic *** this article,we propose a novel enumeration justification algorithm,working with a replicated *** replicated driver discovers new justifications from the explored justifications through cheap literals resolution,which avoids frequent calls of SAT ***,when the use of SAT solver is inevitable,we adjust the strategies and heuristic parameters of the built-in SAT solver of axiom pinpointing *** adjusted SAT solver is able to improve the checking efficiency of unexplored *** proposed method is implemented as a tool named *** experimental results show that RDMinA outperforms the existing axiom pinpointing tools on practical biomedical ontologies such as Gene,Galen,NCI and Snomed-CT.

关键词： axiom pinpointing description logic SAT solver

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Optimizing Deep Learning for Brain Pathology Detection Using SqueezeNet with CT Imaging

Optimizing Deep Learning for Brain Pathology Detection Using...

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2024 IEEE International Conference on Signal Processing and Advance Research in Computing, SPARC 2024

作者： Natarajan, Suresh Kumar Ghantasala, G S Pradeep Anthoniraj, S. Vidyullatha, Pellakuri Rajesh Sharma, R. Ananthanagu, U. School of Computer Science and Engineering Ramanagara India Alliance University Alliance College of Engineering and Design Department of Computer Science and Engineering Bengaluru India Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Andhra Pradesh Vaddeswaram Guntur India

ISBN: (纸本)9798350385199

In this research, a explore the realm of medical imaging, specifically focusing on early brain pathology detection through the lens of deep learning. The primary objective is to optimize SqueezeNet, lightweight convolutional neural network architecture, for brain pathology detection using CT imaging. The motivation stems from the critical need for accurate and swift identification of brain abnormalities, with potential implications for patient outcomes. The meticulously preprocess a dataset of CT images of the human brain to enhance the model's ability to discern subtle pathology patterns. SqueezeNet, known for its efficiency, is employed, and optimization techniques during training enhance its performance. These findings suggest SqueezeNet's potential as a valuable tool in the medical field, offering a balance between efficiency and diagnostic accuracy. Throughout the discussion, A critically analyzes the implications of results, drawing comparisons with existing literature and addressing any encountered limitations. In this research contributes to the discourse on leveraging deep learning for brain pathology detection and the experimental results showcase promising outcomes, with a test accuracy of 78%. Precision, recall, and F1-score metrics indicate the model's proficiency in distinguishing between different pathologies: 87% for Hemorrhagic, 70% for Ischemic, and 79% for Normal cases. Confusion matrices and ROC curves provide comprehensive insights into the model's classification capabilities. The optimized SqueezeNet application demonstrates promise in enhancing diagnostic capabilities, with the obtained results providing valuable insights for future advancements in the intersection of deep learning and medical imaging, potentially impacting patient care and outcomes positively. © 2024 IEEE.

关键词： Medical imaging

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