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MediServe:An IoT-Enhanced Deep Learning Framework for Personalized Medication Management for Elderly Care

computers, Materials & Continua 2025年第4期83卷 935-976页

作者： Smita Kapse Ganesh Yenurkar Vincent Omollo Nyangaresi Gunjan Balpande Shravani Kale Manthan Jadhav Sahil Lawankar Vikrant Jaunjale Department of Computer Technology Yeshwantrao Chavan College of EngineeringWanadongariNagpur441110MaharashtraIndia Computer Science&Engineering Jaramogi Oginga Odinga University of Science&TechnologyBondo40601Kenya Department of Applied Electronics Saveetha School of EngineeringSIMATSChennai602105TamilnaduIndia

In today’s fast-paced world,many elderly individuals struggle to adhere to their medication schedules,especially those with memory-related conditions like Alzheimer’s disease,leading to serious health risks,hospital-izations,and increased healthcare *** reminder systems often fail due to a lack of personalization and real-time *** address this critical challenge,we introduce MediServe,an advanced IoT-enabled medication management system that seamlessly integrates deep learning techniques to provide a personalized,secure,and adaptive *** features a smart medication box equipped with biometric authentication,such as fingerprint recognition,ensuring authorized access to prescribed medication while preventing misuse.A user-friendly mobile application complements the system,offering real-time notifications,adherence tracking,and emergency alerts for caregivers and healthcare *** system employs predictive deep learning models,achieving an impressive classification accuracy of 98%,to analyze user behavior,detect anomalies in medication adherence,and optimize scheduling based on an individual’s habits and health ***,MediServe enhances accessibility by employing natural language processing(NLP)models for voice-activated interactions and text-to-speech capabilities,making it especially beneficial for visually impaired users and those with cognitive ***-based data analytics and wireless connectivity facilitate remote monitoring,ensuring that caregivers receive instant alerts in case of missed doses or medication ***,machine learning-based clustering and anomaly detection refine medication reminders by adapting to users’changing health *** combining IoT,deep learning,and advanced security protocols,MediServe delivers a comprehensive,intelligent,and inclusive solution for medication *** innovative approach not only improves the quality of life for elderly

关键词： MediServe medication health risks smart medication box

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Towards intelligent and trustworthy task assignments for 5G-enabled industrial communication systems

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Digital Communications and Networks 2025年第1期11卷 246-255页

作者： Mingfeng Huang Anfeng Liu Neal N.Xiong Athanasios V.Vasilakos School of Computer and Communication Engineering Changsha University of Science&TechnologyChangsha410114China School of Electronic Information Central South UniversityChangsha410083China Department of Computer Science and Mathematics Sul Ross State UniversityAlpineTX 79830USA College of Mathematics and Computer Science Fuzhou UniversityFuzhou350116China Center for AI Research University of AgderGrimstad 999026Norway

With the unprecedented prevalence of Industrial Internet of Things(IIoT)and 5G technology,various applications supported by industrial communication systems have generated exponentially increased processing tasks,which makes task assignment inefficient due to insufficient *** this paper,an Intelligent and Trustworthy task assignment method based on Trust and Social relations(ITTS)is proposed for scenarios with many tasks and few ***,ITTS first makes initial assignments based on trust and social influences,thereby transforming the complex large-scale industrial task assignment of the platform into the small-scale task assignment for each ***,an intelligent Q-decision mechanism based on workers'social relation is proposed,which adopts the first-exploration-then-utilization principle to allocate *** when a worker cannot cope with the assigned tasks,it initiates dynamic worker recruitment,thus effectively solving the worker shortage problem as well as the cold start *** importantly,we consider trust and security issues,and evaluate the trust and social circles of workers by accumulating task feedback,to provide the platform a reference for worker recruitment,thereby creating a high-quality worker ***,extensive simulations demonstrate ITTS outperforms two benchmark methods by increasing task completion rates by 56.49%-61.53%and profit by 42.34%-47.19%.

关键词： Industrial Internet of Things Insufficient workers Trust evaluation Social relation Task assignment

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Machine learning strategies for small sample size in materials science

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science China Materials 2025年第2期68卷 387-405页

作者： Qiuling Tao JinXin Yu Xiangyu Mu Xue Jia Rongpei Shi Zhifu Yao Cuiping Wang Haijun Zhang Xingjun Liu School of Materials Science and Engineering and Institute of Materials Genome&Big DataHarbin Institute of TechnologyShenzhenShenzhen 518055China School of Computer Science&Technology Harbin Institute of TechnologyShenzhenShenzhen 518055China Advanced Institute for Materials Research(WPI-AIMR) Tohoku UniversitySendai 980-8577Japan Department of Materials Science and Engineering College of MaterialsXiamen UniversityXiamen 361005China State Key Laboratory of Advanced Welding and Joining Harbin Institute of TechnologyShenzhenShenzhen 518055China

Machine learning (ML) has been widely used todesign and develop new materials owing to its low computational cost and powerful predictive capabilities. In recentyears, the shortcomings of ML in materials science have gradually emerged, with a primary concern being the scarcity ofdata. It is challenging to build reliable and accurate ML modelsusing limited data. Moreover, the small sample size problemwill remain long-standing in materials science because of theslow accumulation of material data. Therefore, it is importantto review and categorize strategies for small-sample learningfor the development of ML in materials science. This reviewsystematically sorts the research progress of small-samplelearning strategies in materials science, including ensemblelearning, unsupervised learning, active learning, and transferlearning. The directions for future research are proposed, including few-shot learning, and virtual sample *** importantly, we emphasize the significance of embedding material domain knowledge into ML and elaborate on thebasic idea for implementing this strategy.

关键词： material design machine learning small sample size few-shot learning material domain knowledge

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Enhancing Solar Photovoltaic Efficiency:A Computational Fluid Dynamics Analysis

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Energy Engineering 2025年第1期122卷 153-166页

作者： Rahool Rai Fareed Hussain Mangi Kashif Ahmed Sudhakar Kumaramsay Faculty of Mechanical and Automotive Engineering Universiti Malaysia Pahang Al-Sultan AbdullahPekan26600PahangMalaysia Faculty of Engineering Science&Technology Hamdard UniversityKarachi74600Pakistan Electrical Engineering Department SUKKUR IBA UniversitySukkur65200Pakistan Berlin School of Business and Innovation BSBI Faculty of Computer Science and InformaticsBerlin12043Germany Automotive Engineering Centre University Malaysia Pahang Al Sultan AbdullahPekan26600PahangMalaysia Centre for Research in Advanced Fluid&Processes(Fluid Centre) Universiti Malaysia Pahang Al-Sultan Abdullah(UMPSA)Paya BesarKuantan26300PahangMalaysia

The growing need for sustainable energy solutions,driven by rising energy shortages,environmental concerns,and the depletion of conventional energy sources,has led to a significant focus on renewable *** energy,among the various renewable sources,is particularly appealing due to its abundant ***,the efficiency of commercial solar photovoltaic(PV)modules is hindered by several factors,notably their conversion efficiency,which averages around 19%.This efficiency can further decline to 10%–16%due to temperature increases during peak sunlight *** study investigates the cooling of PV modules by applying water to their front surface through Computational fluid dynamics(CFD).The study aimed to determine the optimal conditions for cooling the PV module by analyzing the interplay between water film thickness,Reynolds number,and their effects on temperature reduction and heat *** CFD analysis revealed that the most effective cooling condition occurred with a 5 mm thick water film and a Reynolds number of *** specific parameters were found to maximize the heat transfer and temperature reduction *** finding is crucial for the development of practical and efficient cooling systems for PV modules,potentially leading to improved performance and longevity of solar *** cooling fluids or advanced cooling techniques that might offer even better efficiency or practical benefits.

关键词： PV module efficiency water film thickness reynolds number CFD analysis PV/T renewable energy

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The Case of Using Multiple Streams in Streaming

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International Journal of Automation and computing 2013年第6期10卷 587-596页

作者： Muhammad Abid Mughal Hai-Xia Wang Dong-Sheng Wang Tsinghua National Laboratory for Information Science and Technology Department of Computer Science&TechnologyTsinghua University

Off-chip replacement （capacity and conflict） and coherent read misses in a distributed shared memory system cause execution to stall for hundreds of cycles. These off-chip replacement and coherent read misses are recurring and forming sequences of two or more misses called streams. Prior streaming techniques ignored reordering of misses and not-recently-accessed streams while streaming data. In this paper, we present stream prefetcher design that can deal with both problems. Our stream prefetcher design utilizes stream waiting rooms to store not-recently-accessed streams. Stream waiting rooms help remove more off-chip misses. Using trace based simulation% our stream prefetcher design can remove 8% to 66% （on average 40%） and 17% to 63% （on average 39%） replacement and coherent read misses, respectively. Using cycle-accurate full-system simulation, our design gives speedups from 1.00 to 1.17 of princeton application repository for shared-memory computers （PARSEC） workloads running on a distributed shared memory system with the exception of dedup and swaptions workloads.

关键词： Prefetching stream first in first out (FIFO) princeton application repository for shared-memory computers (PARSEC),stream waiting rooms reordering of misses sequitur.

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Deep Learning for Object Detection:A Survey

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computer Systems science & Engineering 2021年第8期38卷 165-182页

作者： Jun Wang Tingjuan Zhang Yong Cheng Najla Al-Nabhan Science and Technology Industry Department Nanjing University of Information Science&Technology210044China School of Computer&Software Jiangsu Engineering Center of Network MonitoringNanjing University of Information Science&Technology210044China Department Computer Science King Saud UniversityRiyadhKSA

Object detection is one of the most important and challenging branches of computer vision,which has been widely applied in people s life,such as monitoring security,autonomous driving and so on,with the purpose of locating instances of semantic objects of a certain *** the rapid development of deep learning algorithms for detection tasks,the performance of object detectors has been greatly *** order to understand the main development status of target detection,a comprehensive literature review of target detection and an overall discussion of the works closely related to it are presented in this *** paper various object detection methods,including one-stage and two-stage detectors,are systematically summarized,and the datasets and evaluation criteria used in object detection are *** addition,the development of object detection technology is ***,based on the understanding of the current development of target detection,we discuss the main research directions in the future.

关键词： Object detection convolutional neural network computer vision

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RP-NBSR: A Novel Network Attack Detection Model Based on Machine Learning

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computer Systems science & Engineering 2021年第4期37卷 121-133页

作者： Zihao Shen Hui Wang Kun Liu Peiqian Liu Menglong Ba MengYao Zhao School of Computer Science&Technology Henan Polytechnic UniversityJiaozuo Henan454000China College of Computer Science&Technology Jilin UniversityChangchun Jilin130012China Department of Computer Science University College LondonLondonUnited Kingdom

The rapid progress of the Internet has exposed networks to an increasednumber of threats. Intrusion detection technology can effectively protect networksecurity against malicious attacks. In this paper, we propose a ReliefF-P-NaiveBayes and softmax regression (RP-NBSR) model based on machine learningfor network attack detection to improve the false detection rate and F1 score ofunknown intrusion behavior. In the proposed model, the Pearson correlation coef-ficient is introduced to compensate for deficiencies in correlation analysis betweenfeatures by the ReliefF feature selection algorithm, and a ReliefF-Pearson correlation coefficient (ReliefF-P) algorithm is proposed. Then, the Relief-P algorithm isused to preprocess the UNSW-NB15 dataset to remove irrelevant features andobtain a new feature subset. Finally, naïve Bayes and softmax regression (NBSR)classifier is constructed by cascading the naïve Bayes classifier and softmaxregression classifier, and an attack detection model based on RP-NBSR is established. The experimental results on the UNSW-NB15 dataset show that the attackdetection model based on RP-NBSR has a lower false detection rate and higherF1 score than other detection models.

关键词： Naïve Bayes softmax regression machine learning ReliefF-P attack detection

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New collision detection method for simulating virtual plant populations

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International Journal of Agricultural and Biological Engineering 2019年第6期12卷 156-161页

作者： Weilong Ding Zangxin Wan Yan Xu Nelson Max College of Computer Science&Technology Zhejiang University of TechnologyHangzhou 310026China Department of Computer Science University of CaliforniaDavis95616USA

Detecting and resolving the collision of organs between different plants or the collision of different organs of a single plant are key issues in the realistic construction of a virtual plant population.A suitable collision detection scheme is necessary to prevent a reduction in realism caused by organ penetration.A mixed bounding volume tree construction scheme based on the growth characteristics of tomato plants is proposed in this paper,and the construction mode of the bounding at all levels is simplified by using a digital tomato *** a parallel GPU approach,we designed a tomato plant population collision detection program with CUDA *** proposed method reduces the total collision detection time by 92%-96%.

关键词： plant simulation collision detection bounding volume GPU processing

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Provably secure authentication protocol for traffic exchanges in unmanned aerial vehicles

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High-Confidence Computing 2023年第4期3卷 60-72页

作者： Vincent Omollo Nyangaresi Department of Computer Science&Software Engineering Jaramogi Oginga Odinga University of Science&TechnologyKenya

Unmanned aerial vehicles offer services such as military reconnaissance in potentially adversarial controlled *** addition,they have been deployed in civilian critical infrastructure *** this environment,real-time and massive data is exchanged between the aerial vehicles and the ground control *** on the mission of these aerial vehicles,some of the collected and transmitted data is sensitive and ***,many security protocols have been presented to offer privacy and security ***,majority of these schemes fail to consider attack vectors such as side-channeling,de-synchronization and known secret session temporary information *** last attack can be launched upon adversarial physical capture of these *** addition,some of these protocols deploy computationally intensive asymmetric cryptographic primitives that result in high *** this paper,an authentication protocol based on lightweight quadratic residues and hash functions is *** formal security analysis is executed using the widely deployed random oracle *** addition,informal security analysis is carried out to show its robustness under the Dolev–Yao(DY)and Canetti–Krawczyk(CK)threat *** terms of operational efficiency,it is shown to have relatively lower execution time,communication costs,and incurs the least storage costs among other related ***,the proposed protocol provides a 25%improvement in supported security and privacy features and a 6.52%reduction in storage *** overall,the proposed methodology offers strong security and privacy protection at lower execution time,storage and communication overheads.

关键词： Authentication Drones Quadratic residues Privacy Security Side-channeling UAV

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Optimization method to obtain appropriate spacing parameters for crop cultivation

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International Journal of Agricultural and Biological Engineering 2020年第1期13卷 146-152页

作者： Weilong Ding Chengcheng Fan Lifeng Xu Tao Xie Yang Liu Zangxin Wan Nelson Max College of Computer Science&Technology Zhejiang University of TechnologyHangzhou 310026China Department of Computer Science University of CaliforniaDavisCA 95616USA

Considering the time-consuming and tedious work of the current methods to control plant layout,which is mostly based on expert experience or field trials,we propose an algorithm to optimize and simulate a planting layout based on a virtual plant model and an optimization algorithm.A functional-structural plant model,which combines the structure and physiological function of plants,is used to construct a planting *** planting and row spacing are set as the genetic factors and the chromosomes of the genetic algorithm are encoded with a binary *** photosynthetic yield of the unit planting area is denoted as the fitness *** using this method,the intercropping of maize and soybean plants and the sole cropping of rice plants are *** results show that the proposed method can obtain a high yield planting plan.

关键词： functional-structural plant models genetic algorithm spacing optimization plant spatial distribution

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