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Age of Semantics in Cooperative Communications: To Expedite Simulation Towards Real via Offline Reinforcement Learning

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IEEE Transactions on Network science and Engineering 2025年

作者： Chen, Xianfu Zhao, Zhifeng Mao, Shiwen Wu, Celimuge Zhang, Honggang Bennis, Mehdi Shenzhen CyberAray Network Technology Co. Ltd. Shenzhen518100 China Zhejiang University Zhejiang Lab Hangzhou310027 China Zhejiang University College of Information Science and Electronic Engineering Hangzhou310027 China Auburn University Department of Electrical and Computer Engineering AuburnAL36849 United States The University of Electro-Communications Meta-Networking Research Center Chofu-shi Tokyo182-8585 Japan The University of Electro-Communications Graduate School of Informatics and Engineering Chofu-shi Tokyo182-8585 Japan City University of Macau Faculty of Data Science Taipa999078 China University of Oulu Centre for Wireless Communications Oulu90570 Finland

The age of information metric fails to correctly describe the intrinsic semantics of a status update. In an intelligent reflecting surface-aided cooperative relay communication system, we propose the age of semantics (AoS) for measuring the semantics freshness of status updates. Specifically, we focus on status updates from a source node (SN) to the destination, which is formulated as a Markov decision process. The objective of the SN is to maximize the expected satisfaction of AoS and energy consumption under the maximum transmit power constraint. To seek the optimal control policy, we first derive an online deep actor-critic (DAC) learning scheme under the on-policy temporal difference learning framework. However, implementing the online DAC in practice poses key challenge in infinitely repeated interactions between the SN and the system, which can be dangerous particularly during exploration. We then put forward a novel offline DAC scheme, which estimates the optimal control policy from a previously collected dataset without any further interactions with the system. Numerical experiments verify the theoretical results and show that our offline DAC scheme significantly outperforms the online DAC scheme and the most representative baselines in terms of mean utility, demonstrating strong robustness to dataset quality. © 2013 IEEE.

关键词： Deep reinforcement learning

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Non-local piezoelasticity to incorporate the influence of small-scale factors on the resonance behavior of the Mindlin piezoelectric polymeric nanoplates

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Case Studies in Chemical and Environmental Engineering 2025年 11卷

作者： Sawaran Singh, Narinderjit Singh Hassan, Waqed H. Ameen Ahmed, Zainab Mоhammed Al-zahy, Younis Mohamed Atiah Salahshour, Soheil Pirmoradian, Mostafa Faculty of Data Science and Information Technology INTI International University Persiaran Perdana BBN Putra Nilai Nilai 71800 Malaysia University of Warith Al-Anbiyaa Kerbala 56001 Iraq Department of Civil Engineering College of Engineering University of Kerbala Kerbala 56001 Iraq Department of basic sciences College of Nursing university of kirkuk Iraq Department of Physics College of Education Misan University Maysan Iraq Faculty of Engineering and Natural Sciences Istanbul Okan University Istanbul Türkiye Faculty of Engineering and Natural Sciences Bahcesehir University Istanbul Türkiye Faculty of Science and Letters Piri Reis University Tuzla Istanbul Türkiye Department of Mechanical Engineering Khomeinishahr branch Islamic Azad University Khomeinishahr Iran

This study presents an investigation into the vibration resonance of Mindlin piezoelectric polymeric nanoplates under electromechanical loading, particularly in the presence of a rotating nanoparticle. The novelty of this research lies in the application of non-local piezoelasticity, which effectively incorporates the influence of small-scale factors on the resonance behavior of the nanoplate. By employing a variational approach to derive the governing equations, this work advances the understanding of how various parameters such as the non-local parameter, dimensions of the nanoplate, excitation voltage, and mass of the nanoparticle affect resonance frequencies. The Galerkin method is utilized to solve the partial differential equations governing the dynamics of the piezoelectric polymeric nanoplate, marking a significant methodological contribution to the field. The incremental harmonic balance approach is then applied to estimate the system's resonance frequencies, with numerical simulations confirming their existence. This research not only elucidates the complex interactions affecting resonance behavior but also highlights the potential for optimizing the design of nanostructures in various applications, including sensors and energy-harvesting devices. The findings suggest that increasing the non-local parameter softens the nanoplate's rigidity, leading to decreased resonance frequencies, while modifications in dimensions and applied voltages can enhance these frequencies. Overall, this study lays the groundwork for future explorations into the dynamic behavior of piezoelectric materials, emphasizing the importance of small-scale effects in nanotechnology applications. © 2025 The Authors

关键词： Elastic nanoplate Incremental harmonic balance method Moving nanoparticle Piezoelectric polymeric material Vibration resonance

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Carbon-doped percentage effect on the mechanical properties of nanoporous silicon sample using molecular dynamics simulation

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Case Studies in Chemical and Environmental Engineering 2025年 11卷

作者： Sawaran Singh, Narinderjit Singh Ali, Ali B.M. Ameen, Hawzhen Fateh M. Al-Zahiwat, Murtadha M. Salahshour, Soheil Emami, Nafiseh Faculty of Data Science and Information Technology INTI International University Persiaran Perdana BBN Putra Nilai Nilai 71800 Malaysia Air Conditioning Engineering Department College of Engineering University of Warith Al-Anbiyaa Karbala Iraq Department of Petroleum Technology Erbil Technology College Erbil Polytechnic University Kurdistan Region Erbil Iraq Department of Petroleum Engineering Knowledge University Erbil Iraq Department of Chemical engineering College of Engineering University of Misan Amarah Iraq Faculty of Engineering and Natural Sciences Istanbul Okan University Istanbul Türkiye Faculty of Engineering and Natural Sciences Bahcesehir University Istanbul Türkiye Research Center of Applied Mathematics Khazar University Baku Türkiye Fast Computing Center Shabihsazan Ati Pars Tehran Iran

Porous materials have attracted considerable attention from researchers due to its many uses in molecular separation, heterogeneous catalysis, absorption technologies, and electronic improvements. These solid materials, often defined by their structural voids, are essential in several sectors. This research investigated the impact of carbon doping on the mechanical characteristics of nanoporous silicon matrices. The use of high-purity silicon doping is very beneficial in the semiconductor industry and is crucial for high-power devices and automotive applications. This study simulates a nanoporous silicon sample by molecular dynamics methods, adding carbon doping at different concentrations. The findings demonstrate that when the carbon doping concentration escalated from 1 % to 30 %, the mechanical resistance of the system decreased correspondingly. The ultimate tensile strength fell from 10.26 to 9.02 GPa. Furthermore, Young's modulus rose from 83.47 to 98.37 GPa. The decline in mechanical stability was associated with a drop in the model's total weight, which had considerable ramifications for industrial applications. Thus, incorporating C-doped nanoporous silicon into real applications not only lowered the weight of target materials but also improved their use. © 2025 The Author(s)

关键词： Carbon doping Mechanical properties Molecular dynamics simulation Nanoporous Porous materials

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Chronic atrophic gastritis detection with a convolutional neural network considering stomach regions

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World Journal of Gastroenterology 2020年第25期26卷 3650-3659页

作者： Misaki Kanai Ren Togo Takahiro Ogawa Miki Haseyama Graduate School of Information Science and Technology Hokkaido UniversitySapporo 0600814HokkaidoJapan Education and Research Center for Mathematical and Data Science Hokkaido UniversitySapporo 0600812HokkaidoJapan Faculty of Information Science and Technology Hokkaido UniversitySapporo 0600814HokkaidoJapan

BACKGROUND The risk of gastric cancer increases in patients with Helicobacter pylori-associated chronic atrophic gastritis(CAG).X-ray examination can evaluate the condition of the stomach,and it can be used for gastric cancer mass ***,skilled doctors for interpretation of X-ray examination are decreasing due to the diverse of *** To evaluate the effectiveness of stomach regions that are automatically estimated by a deep learning-based model for CAG *** We used 815 gastric X-ray images(GXIs)obtained from 815 *** ground truth of this study was the diagnostic results in X-ray and endoscopic *** a part of GXIs for training,the stomach regions are manually annotated.A model for automatic estimation of the stomach regions is trained with the *** the rest of them,the stomach regions are automatically ***,a model for automatic CAG detection is trained with all GXIs for *** In the case that the stomach regions were manually annotated for only 10 GXIs and 30 GXIs,the harmonic mean of sensitivity and specificity of CAG detection were 0.955±0.002 and 0.963±0.004,*** By estimating stomach regions automatically,our method contributes to the reduction of the workload of manual annotation and the accurate detection of the CAG.

关键词： Gastric cancer risk Chronic atrophic gastritis Helicobacter pylori Gastric Xray images Deep learning Convolutional neural network Computer-aided diagnosis

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A Predictive Model for Preliminary Indication of Cardiovascular Disease

A Predictive Model for Preliminary Indication of Cardiovascu...

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2022 International Conference on Emerging Trends in Smart Technologies, ICETST 2022

作者： Arif, Ali Haider Bukhari, Faisal Fatima, Aimen Iqbal, Waheed University of the Punjab Faculty of Computing and Information Technology Department of Computer Science Lahore Pakistan University of the Punjab Faculty of Computing and Information Technology Department of Data Science Lahore Pakistan

ISBN: (数字)9781665459358

ISBN: (纸本)9781665459358

Executing medical diagnoses appropriately and effectively is critical due to the scarcity of available resources in the hospitals of developing countries. Diagnosis is also rendered by professional practice and expertise. Because of this, patients bear unnecessary and disproportionate care costs. The automated system is very beneficial for medical diagnosis. As in some cases, there could be a shortage of resource personnel, and not all doctors have experience in subspecialties. We needed studies of various available techniques and their comparisons for implementing these accurate automated systems. The current research, however, is an alternative precaution to this issue. A preliminary indication of cardiovascular disease using a predictive model is essential as it reduces the risk of developing the disease. The likelihood of having the cardiovascular disease can be predicted using multiple factors. One thousand sixty samples of individuals were taken from different hospitals in Punjab by using a questionnaire survey. Other scaling techniques were applied to the collected data. Various machine learning algorithms with hyperparameter tuning were applied to the collected data. As the results of the predictions were satisfactory, it would help predict cardiovascular disease and act as a critical public awareness to avoid future cardiac disease. © 2022 IEEE.

关键词： Diagnosis

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Development of Low-Cost Surgical Simulator for Neuroendoscopy using Unity3D and HTC VIVE 16

Development of Low-Cost Surgical Simulator for Neuroendoscop...

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16th International Conference on Open Source Systems and Technologies, ICOSST 2022

作者： Fatima, Aimen Bukhari, Faisal Iqbal, Waheed University of the Punjab Faculty of Computing and Information Technology Department of Computer Science Lahore Pakistan University of the Punjab Faculty of Computing and Information Technology Department of Data Science Lahore Pakistan

ISBN: (纸本)9781665464772

Neuroendoscopy is being utilized more frequently to treat brain tumors and hydrocephalus brought on by tumors. Neuroendoscopy is a minimally invasive operation that requires a lot of skills. Complete training is needed in hospitals to perform this procedure in the operating room. Simulators are necessary to train doctors due to the deficiency of time, resources, cost, and potential risks. With advancements in computer technology, it is becoming more common to simulate and plan surgery using a VR-based simulation. We have created and developed a surgical simulator to provide endoscopic training for the ETV procedure. A method to use multimedia capabilities for learning is to create a virtual 3D simulator using a game engine and render it using VR technology. The user-friendly collaborative environment of the Unity3D game engine offers good features. We have demonstrated how a simplex mesh depiction in a game-based simulator may effectively deform a soft body in actuality. We have successfully developed a method employing Position Based Dynamics to simulate the actual deformation of TM the cancerous brain. According to our study, the HTC Vive is a suitable VR technology for ETV training because it offers excellent precision, quick tactile feedback, a fast frame rate, and a wide field of vision. In the future, this practical tool might replace more costly training simulators. © 2022 IEEE.

关键词： Tumors

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A Quantum Tanimoto Coefficient Fidelity for Entanglement Measurement

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IEEE/CAA Journal of Automatica Sinica 2023年第2期10卷 439-450页

作者： Yangyang Zhao Fuyuan Xiao Masayoshi Aritsugi Weiping Ding the School of Big Data and Software Engineering Chongqing UniversityChongqing 401331China IEEE the Faculty of Advanced Science and Technology Kumamoto UniversityKumamoto 860-8555Japan the School of Information and Technology Nantong UniversityNantong 223019China

Fidelity plays an important role in quantum information processing,which provides a basic scale for comparing two quantum *** present,one of the most commonly used fidelities is Uhlmann-Jozsa(U-J)***,U-J fidelity needs to calculate the square root of the matrix,which is not trivial in the case of large or infinite density ***,U-J fidelity is a measure of overlap,which has limitations in some cases and cannot reflect the similarity between quantum states ***,a novel quantum fidelity measure called quantum Tanimoto coefficient(QTC)fidelity is proposed in this *** other existing fidelities,QTC fidelity not only considers the overlap between quantum states,but also takes into account the separation between quantum states for the first time,which leads to a better performance of ***,we discuss the properties of the proposed QTC *** fidelity is compared with some existing fidelities through specific examples,which reflects the effectiveness and advantages of QTC *** addition,based on the QTC fidelity,three discrimination coefficients d_(1)^(QTC),d_(2)^(QTC),and d_^(3)^(QTC)are defined to measure the difference between quantum *** is proved that the discrimination coefficient d_(3)^(QTC)is a true ***,we apply the proposed QTC fidelity-based discrimination coefficients to measure the entanglement of quantum states to show their practicability.

关键词： Distance measure entanglement measurement fidelity measure quantum Tanimoto coefficient(QTC) similarity measure uncertainty

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Vehicle and driver scheduling modelling: A case study in UKM

Vehicle and driver scheduling modelling: A case study in UKM

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2009 2nd Conference on data Mining and Optimization, DMO 2009

作者： Oughalime, Ahmed Ismail, Wan Rosmanira Liong, Choong-Yeun Ayob, Masri School of Mathematical Sciences Faculty of Science and Technology Malaysia Data Mining and Optimisation Research Group Department of Computer Science Faculty of Information Science and Technology Malaysia

ISBN: (纸本)9781424449446

This paper deals with the vehicle and driver scheduling problems at UKM transportation department. Given daily sets of trips, drivers and non homogenous vehicles fleet, the aim is to schedule the resources in order to cover, if possible, all the trip demands. The problem formulation has been done using sequential approach where an integer programming and goal programming models have been presented respectively for vehicle scheduling problem and driver scheduling problem. © 2009 IEEE.

关键词： Integer programming

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Implementing Hadoop and Moodle Integrated Student Support System 5

Implementing Hadoop and Moodle Integrated Student Support Sy...

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5th International Conference on Advanced information Technologies, ICAIT 2024

作者： Aung, Myint Myat Min Htet, Shin Set, Hein Myo Hpone Thant, Aung Htut, Sithu Htet, Kyaw Zin Nwe Myint Thein, Nwe University of Information Technology Data Distribution Management Lab Yangon Myanmar University of Information Technology Data Distribution Management Lab Faculty of Computer Science Yangon Myanmar

ISBN: (纸本)9798331510046

Learning management systems (LMS) generate large amounts of real-time data which has the potential to provide valuable insights. Hadoop MapReduce is a scalable framework that is designed to handle such data. This paper presents a system architecture that integrates Hadoop MapReduce into Moodle, a popular LMS, for analyzing academic data. The implementation of the architecture allows users to generate a variety of reports from student attendance logs through a Moodle plugin which utilizes the Hadoop cluster for processing data. Users such as lecturers can then utilize these reports to identify which students do and do not engage in which courses as well as monitor their eligibility for exams. The use of Hadoop MapReduce provides high performance computing (HPC) capabilities that offer distributed parallel processing and economical scalability by means of adding commodity nodes to the cluster. © 2024 IEEE.

关键词： MapReduce

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Optimizing Clustering Approaches in Cloud Environments

International Journal of Interactive Mobile Technologies

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International Journal of Interactive Mobile Technologies 2023年第19期17卷 70-94页

作者： Al-Ghuwairi, Abdel-Rahman Al-Fraihat, Dimah Sharrab, Yousef Kreishan, Yazeed Alsarhan, Ayoub Idhaim, Hasan Qahmash, Ayman Department of Software Engineering Faculty of Prince Al-Hussein Bin Abdallah II for Information Technology The Hashemite University Zarqa Jordan Department of Software Engineering Faculty of Information Technology Isra University Amman Jordan Department of Data Science and Artificial Intelligence Faculty of Information Technology Isra University Amman Jordan Department of Information Technology Faculty of Prince Al-Hussein Bin Abdallah II for Information Technology The Hashemite University Zarqa Jordan Department of Information Systems Faculty of Prince Al-Hussein Bin Abdallah II for Information Technology The Hashemite University Zarqa Jordan Department of Information Systems Computer Science College King Khalid University Abha Saudi Arabia

This study focuses on the challenge of developing abstract models to differentiate various cloud resources. It explores the advancements in cloud products that offer specialized services to meet specific external needs. The study proposes a new approach to request processing in clusters, improving downtime, load distribution, and overall performance. A comparison of three clustering approaches is conducted: local single cluster, local multiple clusters, and multiple cloud clusters. Performance, scalability, fault tolerance, resource allocation, availability, and cost-effectiveness are evaluated through experiments with 50 requests. All three approaches achieve a 100% success rate, but processing times vary. The local single cluster has the longest duration, while the local multiple clusters and multiple cloud clusters perform better and offer faster processing, scalability, fault tolerance, and availability. From a cost perspective, the local single cluster and local multiple clusters incur capital and operational expenses, while the multiple cloud clusters follow a pay-as-you-go model. Overall, the local multiple clusters and multiple cloud clusters outperform the local single cluster in terms of performance, scalability, fault tolerance, resource allocation, availability, and cost-effectiveness. These findings provide valuable insights for selecting appropriate clustering strategies in cloud environments. © 2023 by the authors of this article. Published under CC-BY.

关键词： Fault tolerance

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