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An Efficient ResNetSE Architecture for Smoking Activity Recognition from Smartwatch

Intelligent Automation & Soft Computing 2023年第1期35卷 1245-1259页

作者： narit Hnoohom Sakorn Mekruksavanich Anuchit Jitpattanakul Department of Computer Engineering Image Information and Intelligence LaboratoryFaculty of EngineeringMahidol UniversityNakhon Pathom73170Thailand Department of Computer Engineering School of Information and Communication Technology University of PhayaoPhayao56000Thailand Department of Mathematics Faculty of Applied ScienceKing Mongkut’s University of Technology North BangkokBangkok10800Thailand Intelligent and Nonlinear Dynamic Innovations Research Center Science and Technology Research InstituteKing Mongkut’s University of Technology North BangkokBangkok 10800Thailand

Smoking is a major cause of cancer,heart disease and other afflictions that lead to early *** effective smoking classification mechanism that provides insights into individual smoking habits would assist in implementing addiction treatment *** activities often accompany other activities such as drinking or ***,smoking activity recognition can be a challenging topic in human activity recognition(HAR).A deep learning framework for smoking activity recognition(SAR)employing smartwatch sensors was proposed together with a deep residual network combined with squeeze-and-excitation modules(ResNetSE)to increase the effectiveness of the SAR *** proposed model was tested against basic convolutional neural networks(CNNs)and recurrent neural networks(LStM,BiLStM,GRU and BiGRU)to recognize smoking and other similar activities such as drinking,eating and walking using the Ut-Smoke *** different scenarios were investigated for their recognition performances using standard HAR metrics(accuracy,F1-score and the area under the ROC curve).Our proposed ResNetSE outperformed the other basic deep learning networks,with maximum accuracy of 98.63%.

关键词： Smoking activity recognition deep residual network smartwatch sensors deep learning

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Pre-Impact and Impact Fall Detection Based on a Multimodal Sensor Using a Deep Residual Network

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Intelligent Automation & Soft Computing 2023年第6期36卷 3371-3385页

作者： narit Hnoohom Sakorn Mekruksavanich Anuchit Jitpattanakul Image Information and Intelligence Laboratory Department of Computer EngineeringFaculty of EngineeringMahidol UniversityNakhon Pathom73170Thailand Department of Computer Engineering School of Information and Communication TechnologyUniversity of PhayaoPhayaoThailand Department of Mathematics Faculty of Applied ScienceKing Mongkut’s University of Technology North BangkokBangkok 10800Thailand Intelligent and Nonlinear Dynamic Innovations Research Center Science and Technology Research Institute King Mongkut’s University of Technology North BangkokBangkok 10800Thailand

Falls are the contributing factor to both fatal and nonfatal injuries in the ***,pre-impact fall detection,which identifies a fall before the body collides with the floor,would be ***,researchers have turned their attention from post-impact fall detection to pre-impact fall ***-impact fall detection solutions typically use either a threshold-based or machine learning-based approach,although the threshold value would be difficult to accu-rately determine in threshold-based ***,while additional features could sometimes assist in categorizing falls and non-falls more precisely,the esti-mated determination of the significant features would be too time-intensive,thus using a significant portion of the algorithm’s operating *** this work,we developed a deep residual network with aggregation transformation called FDSNeXt for a pre-impact fall detection approach employing wearable inertial *** proposed network was introduced to address the limitations of fea-ture extraction,threshold definition,and algorithm *** training on a large-scale motion dataset,the KFall dataset,and straightforward evaluation with standard metrics,the proposed approach identified pre-impact and impact falls with high accuracy of 91.87 and 92.52%,*** addition,we have inves-tigated fall detection’s performances of three state-of-the-art deep learning models such as a convolutional neural network(CNN),a long short-term memory neural network(LStM),and a hybrid model(CNN-LStM).the experimental results showed that the proposed FDSNeXt model outperformed these deep learning models(CNN,LStM,and CNN-LStM)with significant improvements.

关键词： Pre-impact fall detection deep learning wearable sensor deep residual network

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A Comprehensive Evaluation of State-of-the-Art Deep Learning Models for Road Surface type Classification

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Intelligent Automation & Soft Computing 2023年第8期37卷 1275-1291页

作者： narit Hnoohom Sakorn Mekruksavanich Anuchit Jitpattanakul Image Information and Intelligence Laboratory Department of Computer EngineeringFaculty of EngineeringMahidol UniversityNakhon Pathom73170Thailand Department of Computer Engineering School of Information and Communication TechnologyUniversity of PhayaoPhayao56000Thailand Department of Mathematics Faculty of Applied ScienceKing Mongkut’s University of Technology North BangkokBangkok10800Thailand Intelligent and Nonlinear Dynamic Innovations Research Center Science and Technology Research InstituteKing Mongkut’s University of Technology North BangkokBangkok10800Thailand

In recent years,as intelligent transportation systems(ItS)such as autonomous driving and advanced driver-assistance systems have become more popular,there has been a rise in the need for different sources of traffic situation *** classification of the road surface type,also known as the RSt,is among the most essential of these situational data and can be utilized across the entirety of the ItS ***,the benefits of deep learning(DL)approaches for sensor-based RSt classification have been demonstrated by automatic feature extraction without manual *** ability to extract important features is vital in making RSt classification more *** work investigates the most recent advances in DL algorithms for sensor-based RSt classification and explores appropriate feature extraction *** used different convolutional neural networks to understand the functional architecture better;we constructed an enhanced DL model called SE-ResNet,which uses residual connections and squeeze-and-excitation mod-ules to improve the classification *** experiments with a publicly available benchmark dataset,the passive vehicular sensors dataset,have shown that SE-ResNet outperforms other state-of-the-art *** proposed model achieved the highest accuracy of 98.41%and the highest F1-score of 98.19%when classifying surfaces into segments of dirt,cobblestone,or asphalt ***,the proposed model significantly outperforms DL networks(CNN,LStM,and CNN-LStM).the proposed RE-ResNet achieved the classification accuracies of asphalt roads at 98.98,cobblestone roads at 97.02,and dirt roads at 99.56%,respectively.

关键词： Road surface type classification deep learning inertial sensor deep pyramidal residual network squeeze-and-excitation module

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Deep Pyramidal Residual Network for Indoor-Outdoor Activity Recognition Based on Wearable Sensor

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Intelligent Automation & Soft Computing 2023年第9期37卷 2669-2686页

作者： Sakorn Mekruksavanich narit Hnoohom Anuchit Jitpattanakul Department of Computer Engineering School of Information and Communication Technology University of PhayaoPhayao56000Thailand Image Information and Intelligence Laboratory Department of Computer EngineeringFaculty of EngineeringMahidol UniversityNakhon Pathom73170Thailand Department of Mathematics Faculty of Applied ScienceKing Mongkut’s University of Technology North BangkokBangkok10800Thailand Intelligent and Nonlinear Dynamic Innovations Research Center Science and Technology Research Institute King Mongkut’s University of Technology North BangkokBangkok10800Thailand

Recognition of human activity is one of the most exciting aspects of time-series classification,with substantial practical and theoretical *** evidence indicates that activity recognition from wearable sensors is an effective technique for tracking elderly adults and children in indoor and outdoor ***,researchers have demon-strated considerable passion for developing cutting-edge deep learning sys-tems capable of exploiting unprocessed sensor data from wearable devices and generating practical decision assistance in many *** study provides a deep learning-based approach for recognizing indoor and outdoor movement utilizing an enhanced deep pyramidal residual model called Sen-PyramidNet and motion information from wearable sensors(accelerometer and gyroscope).the suggested technique develops a residual unit based on a deep pyramidal residual network and introduces the concept of a pyramidal residual unit to increase detection *** proposed deep learning-based model was assessed using the publicly available 19Nonsens dataset,which gathered motion signals from various indoor and outdoor activities,including practicing various body *** experimental findings demon-strate that the proposed approach can efficiently reuse characteristics and has achieved an identification accuracy of 96.37%for indoor and 97.25%for outdoor ***,comparison experiments demonstrate that the SenPyramidNet surpasses other cutting-edge deep learning models in terms of accuracy and ***,this study explores the influence of several wearable sensors on indoor and outdoor action recognition ability.

关键词： Human activity recognition deep learning wearable sensors indoor and outdoor activity deep pyramidal residual network

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Driving Activity Classification Using Deep Residual Networks Based on Smart Glasses Sensors

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Intelligent Automation & Soft Computing 2023年第11期38卷 139-151页

作者： narit Hnoohom Sakorn Mekruksavanich Anuchit Jitpattanakul Department of Computer Engineering Image Information and Intelligence LaboratoryFaculty of EngineeringMahidol UniversityNakhon Pathom73170Thailand Department of Computer Engineering School of Information and Communication TechnologyUniversity of PhayaoPhayaoThailand Department of Mathematics Faculty of Applied ScienceKing Mongkut’s University of Technology North BangkokBangkok10800Thailand Intelligent and Nonlinear Dynamic Innovations Research Center Science and Technology Research InstituteKing Mongkut’s University of Technology North BangkokBangkok10800Thailand

Accidents are still an issue in an intelligent transportation system,despite developments in self-driving technology(ItS).Drivers who engage in risky behavior account for more than half of all road *** a result,reckless driving behaviour can cause congestion and *** vision and multimodal sensors have been used to study driving behaviour categorization to lessen this *** research has also collected and analyzed a wide range of data,including electroencephalography(EEG),electrooculography(EOG),and photographs of the driver’s *** the other hand,driving a car is a complicated action that requires a wide range of body *** this work,we proposed a ResNet-SE model,an efﬁcient deep learning classiﬁer for driving activity clas-siﬁcation based on signal data obtained in real-world trafﬁc conditions using smart ***-to-end learning can be achieved by combining residual networks and channel attention approaches into a single learning *** data from 3-point EOG electrodes,tri-axial accelerometer,and tri-axial gyroscope from the Smart Glasses dataset was utilized in this *** performed various experiments and compared the proposed model to base-line deep learning algorithms(CNNs and LStMs)to demonstrate its *** to the research results,the proposed model outperforms the previous deep learning models in this domain with an accuracy of 99.17%and an F1-score of 98.96%.

关键词： Smart glasses human activity recognition deep learning wearable sensors driving activity

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Impact of Pollutant Concentration and Particle Deposition on the Radiative Flow of Casson-Micropolar Fluid between Parallel Plates

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 665-690页

作者： Ghaliah Alhamzi Badr Saad t.Alkahtani Ravi Shanker Dubey Vinutha Kalleshachar Neelima Nizampatnam Department of Mathematics and Statistics College of ScienceImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11564Saudi Arabia Department of Mathematics College of ScienceKing Saud UniversityRiyadh11989Saudi Arabia Department of Mathematics Amity School of Applied SciencesAmity University RajasthanJaipur302002RajasthanIndia Department of Studies in Mathematics Davangere UniversityDavangere577002India Department of Electronics and Communication Engineering Amrita School of EngineeringAmrita Vishwa VidyapeethamBengaluru560035India

Assessing the behaviour and concentration of waste pollutants deposited between two parallel plates is essential for effective environmental *** the effectiveness of treatment methods in reducing pollution scales is made easier by analysing waste discharge *** waste discharge concentration analysis is useful for assessing how effectively wastewater treatment techniques reduce pollution *** study aims to explore the Casson micropolar fluid flow through two parallel plates with the influence of pollutant concentration and thermophoretic particle *** explore the mass and heat transport features,thermophoretic particle deposition and thermal radiation are *** governing equations are transformed into ordinary differential equations with the help of suitable similarity *** Runge-Kutta-Fehlberg’s fourthfifth order technique and shooting procedure are used to solve the reduced set of equations and boundary *** integration of a neural network model based on the Levenberg-Marquardt algorithm serves to improve the accuracy of predictions and optimize the analysis of *** outcomes are displayed to analyze the characteristics of the relevant dimensionless parameters in the current *** reveal that concentration upsurges as the micropolar parameter *** concentration reduces with an upsurge in the thermophoretic *** upsurge in the external pollutant source variation and the local pollutant external source parameters enhances mass *** surface drag force declines for improved values of porosity and micropolar parameters.

关键词： Micropolar fluid thermal radiation porous medium thermophoretic particle deposition waste discharge concentration

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transport mechanism in chemically reactive hybrid nanofluid flow containing gyrotactic micro-organisms over a curved oscillatory surface

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Applied Mathematics and Mechanics(English Edition) 2025年第1期46卷 177-192页

作者： M.NAVEED M.IMRAN t.ASGHAR Z.ABBAS Department of Mathematics Division of Science and TechnologyUniversity of Education Department of Mathematics The Islamia University of Bahawalpur

this paper examines the transport analysis, including both heat transfer and mass transfer, in hybrid nanofluid flow containing gyrotactic microorganisms towards a curved oscillatory surface. the influence of magnetic fields is also inspected in terms of their physical characteristics. to depict the phenomena of transport, modified versions of both Fick's and Fourier's laws are used. Additionally, the characteristics of both heterogeneous and homogeneous chemical reactions are also incorporated. Utilizing a curvilinear coordinate system, the flow problem is formulated as partial differential equations(PDEs)for momentum, concentration, microorganism field, and energy. An analytical solution to the obtained flow equations is achieved utilizing the homotopy analysis method(HAM).the effects of significant flow parameters on the pressure and microorganism fields, velocity, oscillation velocity, concentration, and temperature distributions are shown via graphs. Furthermore, the variations in skin friction, mass transfer rate, heat transfer rate, and local motile number due to different involved parameters are presented in tables and are analyzed in detail. Graphical results indicate that the curves of velocity and temperature fields are enhanced as the values of the solid volume fraction variables *** is also verified that the concentration rate field decreases as the values of the homogeneous reaction strength parameter and the radius of curvature parameter increase, and it increases with the Schmidt number and the heterogeneous reaction strength *** outcomes show a favorable response of the motile number to advanced values of the Peclet number, the Schmidt number, the microorganism difference parameter, and the bio-convective Lewis number.

关键词： Peclet number

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the impact of alpha-fetoprotein(AFP),child-turcotte-pugh(CtP)score and disease staging on the survival of hepatocellular carcinoma(HCC)patients:a retrospective cohort from single oncology center

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Oncology Research 2025年第1期33卷 149-160页

作者： NASSER MULLA YOUSEF KAtIB ASIM M.ALMUGHAMSI DUAA S.ALKHAYAt MOHAMED MOSAAD SAMIR t.ALFOtIH RAWAN ALAOFI Department of Internal Medicine Faculty of MedicineTaibah UniversityMadinah42278Saudi Arabia Department of Radiology Faculty of MedicineTaibah UniversityMadinah42278Saudi Arabia Department of Surgery Faculty of MedicineTaibah UniversityMadinah42278Saudi Arabia Department of Endemic and Infectious Diseases Suez Canal UniversityIsmailia41522Egypt King Salman bin Abdulaziz Medical City Madinah42311Saudi Arabia Prince Mohammed Bin Abdulaziz Hospital Madinah41511Saudi Arabia

Background:Hepatocellular carcinoma(HCC)is the most common cause of cancer-related death in Saudi *** study aimed to investigate the patterns of HCC and the effect of tNM staging,Alfa-fetoprotein(AFP),and Child-turcotte Pugh(CtP)on patients’overall survival(OS).Methods:A retrospective analysis was conducted on 43 HCC patients at a single oncology center in Saudi Arabia from 2015 to *** patients had to fulfill one of the following criteria:(a)a liver lesion reported as definitive HCC on dynamic imaging and/or(b)a biopsy-confirmed ***:the mean patient age of all HCC cases was 66.8 with a male-to-female ratio of 3.3:*** patients were stratified into two groups:viral HCC(n=22,51%)and non-viral HCC(n=21,49%).Among viral-HCC patients,55%were due to HBV and 45%due to *** was diagnosed in 79%of *** and sex did not significantly statistically differ in OS among viral and non-viral HCC patients(p-value>0.05).About 65%of patients had tumor size>5 cm during the diagnosis,with a significant statistical difference in OS(p-value=0.027).AFP was>400 ng/ml in 45%of the *** was a statistically significant difference in the OS in terms of AFP levels(p-value=0.021).A statistically significant difference was also observed between the CtP score and OS(p-value=0.02).CtP class B had the longest *** was the most common treatment provided to HCC patients followed by sorafenib *** was a significant statistical difference in OS among viral and non-viral HCC patients(p-value=0.008).Conclusions:the most common predictors for OS were the underlying cause of HCC,AFP,and tumor *** having non-viral etiology,a tumor size>5 cm,an AFP>400 ng/mL,and a CtP score class C were all negatively associated with OS.

关键词： Hepatocellular carcinoma Pattern Alpha-fetoprotein(AFP) Child-turcotte-pugh Progression free survival

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Effects of Boesenbergia rotunda （L.） Mansf. on sexual behaviour of male rats

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Asian Journal of Andrology 2007年第6期9卷 849-855页

作者： Paiwan Sudwan Kanokpom Saenphet Salika Aritajat.narit.Sitasuwan Department of Biology Faculty of Science Department of Anatomy Faculty of Medicine Chiang Mai University Chiang Mai 50200 Thailand

Aim： to study the effects of Boesenbergia rotunda （Krachai） on sexual behaviour in male albino rats. Methods： thirty-two male Wistar rats were equally divided into four groups： experimental groups were gavaged with the ethanolic extract of the rhizome of B. rotunda at doses of 60, 120 and 240 mg/kg and a control group received distilled water, for 60 days. Sexual behaviour, reproductive organs, diameter of seminiferous tubule, epididymal sperm density, and androgenic hormones were evaluated. Results： Within 30-min observation, there was no significant difference of courtship behaviour, mount frequency （MF）, intromission frequency （IF）, mount latency （ML）, intromission latency （IL）, copulatory efficiency or intercopulatory interval in male rats. In three 10-min intervals over a 30-min period, courtship behaviour and MF during the first 10-min were significantly higher than those in the second and third i0-min observation in all groups, whereas IF had no significant difference. All doses of B. rotunda extract significantly increased the relative testicular weight and the diameter of the seminiferous tubules. the dose of 60 mg/kg also significantly increased the relative weight of the seminal vesicle. Nevertheless, the sperm density, serum testosterone and androstenedione levels were not affected by the B. rotunda extract. Conclusion： B. rotunda does not affect sexual behaviour nor serum androgenic levels.

关键词： Boesenbergia rotunda sexual behaviour testosterone androstenedione reproductive organ sperm density

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Free vibration and transient response of double curved beams connected by intermediate straight beams

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Applied Mathematics and Mechanics(English Edition) 2025年第1期46卷 37-62页

作者： R.A.JAFARI-tALOOKOLAEI H.GHANDVAR E.JUMAEV S.KHAtIR t.CUONG-LE School of Mechanical Engineering Babol Noshirvani University of Technology Department of Mechanical Engineering Faculty of Engineering New Uzbekistan University University of Business and Science Center for Engineering Application and technology Solutions Ho Chi Minh City Open University

this paper investigates the free vibration and transient response of interconnected structures including double curved beams and intermediate straight beams,which are all constructed from functionally graded porous(FGP) materials. the strain potential and kinetic energies of each beam along with the work done by the external force are calculated. Additionally, a higher-order beam element is introduced to derive stiffness and mass matrices, along with the force vector. the curved and straight beams are discretized, and their assembled stiffness, mass matrices, and force vectors, are *** conditions at the joints are used to derive the total matrices of the entire structure. Subsequently, the natural frequencies and transient response of the system are determined. the accuracy of the mathematical model and the self-developed computer program is validated through the comparison of the obtained results with those of the existing literature and commercial software ANSYS, demonstrating excellent ***, a comprehensive study is conducted to investigate the effects of various parameters on the free vibration and transient response of the considered structure.

关键词： Kinetic energy

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