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Energy Geoscience 2024年第2期5卷 314-320页

作者： uma shankar Department of Geophysics Institute of ScienceBHUVaranasiIndia

Methane gas hydrate related bottom-simulating reflectors(BSRs)are imaged based on the in-line and cross-line multi-channel seismic(MCS)data from the Andaman Forearc *** depth of the BSR depends on pressure and temperature and pore water *** these assumptions,the BSR depth can be used to estimate the geothermal gradient(GTG)based on the availability of in-situ temperature *** calculation is done assuming a 1D conductive model based on available in-situ temperature measurement at site NGHP-01-17 in the study ***,in the presence of seafloor topography,the conductive temperature field in the subsurface is affected by lateral refraction of heat,which focuses heat in topographic lows and away from topographic *** 1D estimate of GTG in the Andaman Forearc Basin has been validated by drilling results from the NGHP-01 expedition.2D analytic modeling to estimate the effects of topography is performed earlier along selected seismic profiles in the study *** study extended to estimate the effect of topography in 3D using a numerical *** corrected GTG data allow us to determine GTG values free of topographic *** difference between the estimated GTG and values corrected for the 3D topographic effect varies up to~5℃/*** conclude that the topographic correction is relatively small compared to other uncertainties in the 1D model and that apparent GTG determined with the 1D model captures the major features,although the correction is needed prior to interpreting subtle features of the derived GTG maps.

关键词： Gas hydrate BSR Geothermal gradient 3D and 2D topographic modeling Andaman Forearc Basin

An Adaptive Scalable Data Pipeline for Multiclass Attack Classification in Large-Scale IoT Networks

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Big Data Mining and Analytics 2024年第2期7卷 500-511页

作者： Selvam Saravanan uma Maheswari Balasubramanian Department of Computer Science and Engineering Amrita School of ComputingAmrita Vishwa VidyapeethamBengaluru 560035India

the current large-scale Internet of things(IoT)networks typically generate high-velocity network traffic *** use IoT devices to create botnets and launch attacks,such as DDoS,Spamming,Cryptocurrency mining,Phishing,*** service providers of large-scale IoT networks need to set up a data pipeline to collect the vast network traffic data from the IoT devices,store it,analyze it,and report the malicious IoT devices and types of ***,the attacks originating from IoT devices are dynamic,as attackers launch one kind of attack at one time and another kind of attack at another *** number of attacks and benign instances also vary from time to *** phenomenon of change in attack patterns is called concept ***,the attack detection system must learn continuously from the ever-changing real-time attack patterns in large-scale IoT network *** meet this requirement,in this work,we propose a data pipeline with Apache Kafka,Apache Spark structured streaming,and MongoDB that can adapt to the ever-changing attack patterns in real time and classify attacks in large-scale IoT *** concept drift is detected,the proposed system retrains the classifier with the instances that cause the drift and a representative subsample instances from the previous training of the *** proposed approach is evaluated with the latest dataset,IoT23,which consists of benign and several attack instances from various IoT *** classification accuracy is improved from 97.8%to 99.46%by the proposed *** training time of distributed random forest algorithm is also studied by varying the number of cores in Apache Spark environment.

关键词： Internet of things(IoT) concept drift Apache Spark MongoDB Apache Kafka streaming

Gas hydrate saturation from NGHP 02 LWD data in the Mahanadi Basin

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Energy Geoscience 2024年第2期5卷 279-289页

作者： uma shankar Pradeep Kumar Yadav Sneha Devi Udham Singh Yadav Department of Geophysics Institute of ScienceBHUVaranasi221005India Oil and Natural Gas Corporation Ltd. Gas Hydrate Research&Technology Centre(GHRTC)Panvel410221Navi MumbaiIndia

During the Indian National Gas Hydrate Program(NGHP)Expedition 02,Logging-while-drilling(LWD)logs were acquired at three sites(NGHP-02-11,NGHP-02-12,and NGHP-02-13)across the Mahanadi Basin in area *** applied rock physics theory to available sonic velocity logs to know the distribution of gas hydrate at site NGHP-02-11 and *** physics modeling using sonic velocity at well location shows that gas hydrate is distributed mainly within the depth intervals of 150-265 m and 100 -215 mbsf at site NGHP-02-11 and NGHP-02-13,respectively,with an average saturation of about 4%of the pore space and the maximum concentration of about 40%of the pore space at 250 m depth at site NGHP-02-11,and at site NGHP-02-13 an average saturation of about 2%of the pore space and the maximum concentration of about 20%of the pore space at 246 m depth,as gas hydrate is distributed mainly within 100-246 mbsf at this *** of gas hydrate estimated from the electrical resistivity method using density derived porosity and electrical resistivity logs from Archie's empirical formula shows high saturation compared to that from the sonic ***,estimates of hydrate saturation based on sonic P-wave velocity may differ significantly from that based on resistivity,because gas and hydrate have higher resistivity than conductive pore fluid and sonic P-wave velocity shows strong effect on gas hydrate as a small amount of gas reduces the velocity significantly while increasing velocity due to the presence of *** site NGHP-02-11,gas hydrate saturation is in the range of 15%e30%,in two zones between 150-180 and 245-265 *** NGHP-02-012 shows a gas hydrate saturation of 20%e30%in the zone between 100 and 207 *** NGHP-02-13 shows a gas hydrate saturation up to 30%in the zone between 215 and 246 *** observations from rock physics modeling and Archie’s approximation show the gas hydrate concentrations are relatively low(the pore space)at the sites of the

关键词： Mahanadi Basin Gas hydrate Sonic log Effective medium modeling Electrical resistivity log Archie’s analysis Gas hydrate saturation

Exploring the Social Impact of the Short-Stay Market(SSM)in Regional Areas:An Empirical Study

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Fudan Journal of the Humanities and Social Sciences 2024年第2期17卷 243-277页

作者： Emeka Ndaguba Kerry Brown Dora Marinova uma Jogulu School of Business and Law Edith Cowan UniversityPerthAustralia Curtin University Sustainability Policy Institute Curtin UniversityPerthAustralia

the discourse on microentrepreneurs and their involvement in the short stay market (SSM) was non-existent until 2008. While several concepts and constructs have been developed and empirically tested since 2009, many of them relate to economics, leaving the social, cultural, and environmental factors underdeveloped. thus, this study aimed to fll the gap and identify and assess the social impact of the short-stay market (SSM) in a regional area. the study included 16 face-to-face interview sessions conducted with 18 participants, and the Leximancer software was employed to analyse the data. the study revealed that the social impact on SSM is not generic, rather pluralistic, multidimensional, and dynamic. the study also found that the limitation clause instituted by the council is a direct disconnect between the council and property owners/managers. Furthermore, despite ample opportunities provided by the short-stay market (SSM) in regional areas, encumbrances cannot be overlooked. therefore, there is a need for a comprehensive approach to understand the social impact on policy frameworks in regional areas.

关键词： Short-stay market Experience economy Long-term rentals Wine economy Regulation

Optimizing Spatial Pattern Analysis in Serial Remote Sensing Images through Empirical Mode Decomposition and Ant Colony Optimization

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Journal of Harbin Institute of Technology(New Series) 2024年第4期31卷 52-60页

作者： J Srinivasan S uma Saleem Raja Abdul Samad Jayabrabu Ramakrishnan Department of Computer Applications Madanapalle Institute of Technology&Science(MITS)Madanapalle 517325Andhra PradeshIndia Department of Information Technology Panimalar Engineering CollegeChennai 600123India Information Technology Department College of Computing and Information SciencesUniversity of Technology and Applied Sciences-Shinas 324Sultanate of Oman Department of Information Technology and Security College of Computer Science and Information TechnologyJazan UniversityJazan 45142Kingdom of Saudi Arabia

Serial remote sensing images offer a valuable means of tracking the evolutionary changes and growth of a specific geographical area over *** the original images may provide limited insights,they harbor considerable potential for identifying clusters and *** aggregation of these serial remote sensing images(SRSI)becomes increasingly viable as distinct patterns emerge in diverse scenarios,such as suburbanization,the expansion of native flora,and agricultural *** a novel approach,we propose an innovative method for extracting sequential patterns by combining Ant Colony Optimization(ACD)and Empirical Mode Decomposition(EMD).this integration of the newly developed EMD and ACO techniques proves remarkably effective in identifying the most significant characteristic features within serial remote sensing images,guided by specific *** findings highlight a substantial improvement in the efficiency of sequential pattern mining through the application of this unique hybrid method,seamlessly integrating EMD and ACO for feature *** study exposes the potential of our innovative methodology,particularly in the realms of urbanization,native vegetation expansion,and agricultural activities.

关键词： spatial pattern analysis EMD ACO

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A single micro-LED manipulation system based on micro-gripper

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Nanotechnology and Precision Engineering 2024年第2期7卷 45-52页

作者： Jie Bai Pingjuan Niu Erdan Gu Jianming Li Clarence Augustine th Tee School of Mechanical Engineering Tiangong University School of Electronic and Information Engineering Tiangong University Institute of Photonics University of Strathclyde Tianjin Key Laboratory of Micro Low Gravity Environment Simulation Technology Tianjin Aerospace Electromechanical Equipment Research Institute Department of Electrical and Information Engineering School of Physics and Electrical Information EngineeringZhejiang Normal University

Micro-LEDs(μLEDs) have advantages in terms of brightness, power consumption, and response speed. In addition, they can also be used as micro-sensors implanted in the body via flexible electronic skin. One of the key techniques involved in the fabrication of μLED-based devices is transfer printing. Although numerous methods have been proposed for transfer printing, improving the yield of μLED arrays is still a formidable task. In this paper, we propose a novel method for improving the yield of μLED arrays transferred by the stamping method, using an innovative design of piezoelectrically driven asymmetric micro-gripper. Traditional grippers are too large to manipulate μLEDs, and therefore two micro-sized cantilevers are added at the gripper tips. A μLED manipulation system is constructed based on the micro-gripper together with a three-dimensional positioning system. Experimental results using this system show that it can be used successfully to manipulate μLED arrays.

关键词： Micro-gripper Micro-LED Transfer printing Manipulation

Significance and Predictive Classification Algorithms in Sentiment Analysis

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Journal of Harbin Institute of Technology(New series) 2024年

作者： V uma V Ganesh Department of Computer and Information Science， Annamalai University Department of Computer Science， Government Arts College (Autonomous) Kumbakonam

In recent times， an abrupt upswing has emerged within the data mining domain， particularly within the sphere of sentiment analysis. Encompassing diverse dimensions such as sentiment extraction， subjectivity categorization， opinion summarization， and spam detection， sentiment analysis， also acknowledged as Opinion Mining (OM)， undertakes a mathematical exploration into the perspectives， emotions， evaluations， and conduct of individuals toward entities， encompassing products， services， individuals， and events. the advent of web technology tools empowers users to liberally articulate their opinions across varied online platforms， culminating in the generation of a substantial corpus of invaluable yet unstructured data. this exposition scrutinizes the importance of harnessing this data， delving into the intricate process of refining and metamorphosing it for subsequent operations like classification and aspect-oriented sentiment analysis. the crux of the discourse centers on a thorough scrutiny of four data mining algorithms deployed for prognostication and categorization， providing insights into their efficacy within the domain of sentiment analysis. this investigation transcends into pragmatic applications， challenges encountered in the field， and potential trajectories ahead， culminating in a nuanced comprehension of the dynamic panorama of sentiment analysis and its ramifications.

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Seasonal Prediction of Indian Summer Monsoon Using WRF: A Dynamical Downscaling Perspective

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Open Journal of Modelling and Simulation 2024年第1期12卷 1-32页

作者： Manas Ranjan Mohanty uma Charan Mohanty Department of Atmospheric and Oceanic Sciences University of California Los Angeles USA Centre for Climate Smart Agriculture Siksha O Anusandhan Deemed to Be University Odisha India

Seasonal forecasting of the Indian summer monsoon by dynamically downscaling the CFSv2 output using a high resolution WRF model over the hindcast period of 1982-2008 has been performed in this study. the April start ensemble mean of the CFSv2 has been used to provide the initial and lateral boundary conditions for driving the WRF. the WRF model is integrated from 1st May through 1st October for each monsoon season. the analysis suggests that the WRF exhibits potential skill in improving the rainfall skill as well as the seasonal pattern and minimizes the meteorological errors as compared to the parent CFSv2 model. the rainfall pattern is simulated quite closer to the observation (IMD) in the WRF model over CFSv2 especially over the significant rainfall regions of India such as the Western Ghats and the central India. Probability distributions of the rainfall show that the rainfall is improved with the WRF. However, the WRF simulates copious amounts of rainfall over the eastern coast of India. Surface and upper air meteorological parameters show that the WRF model improves the simulation of the lower level and upper-level winds, MSLP, CAPE and PBL height. the specific humidity profiles show substantial improvement along the vertical column of the atmosphere which can be directly related to the net precipitable water. the CFSv2 underestimates the specific humidity along the vertical which is corrected by the WRF model. Over the Bay of Bengal, the WRF model overestimates the CAPE and specific humidity which may be attributed to the copious amount of rainfall along the eastern coast of India. Residual heating profiles also show that the WRF improves the thermodynamics of the atmosphere over 700 hPa and 400 hPa levels which helps in improving the rainfall simulation. Improvement in the land surface fluxes is also witnessed in the WRF model.

关键词： Dynamical Downscaling Regional and Mesoscale Modeling Diabatic Heating WRF

A Physical Security Technology Based upon Doubly Multiple Parameters Weighted Fractional Fourier Transform

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China Communications 2024年第10期 200-209页

作者： Li Yong Sun Teng sha Xuejun Song Zhiqun Wang Bin Science and Technology on Communication Networks Laboratory the 54th Research Institute of China Electronics Technology Group Corporation Harbin Institute of Technology

Enhancing the security of the wireless communication is necessary to guarantee the reliable of the data transmission, due to the broadcast nature of wireless channels. In this paper, we provide a novel technology referred to as doubly multiple parameters weighted fractional Fourier transform(DMWFRFT), which can strengthen the physical layer security of wireless communication. this paper introduces the concept of DM-WFRFT based on multiple parameters WFRFT(MP-WFRFT), and then presents its four properties. Based on these properties, the parameters decryption probability is analyzed in terms of the number of parameters. the number of parameters for DM-WFRFT is more than that of the MP-WFRFT,which indicates that the proposed scheme can further strengthen the the physical layer security. Lastly, some numerical simulations are carried out to illustrate that the efficiency of proposed DM-WFRFT is related to preventing eavesdropping, and the effect of parameters variety on the system performance is associated with the bit error ratio(BER).

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STATNet:One-stage coal-gangue detector based on deep learning algorithm for real industrial application

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Energy and AI 2024年第3期17卷 113-125页

作者： Kefei Zhang a Teng Wang Xiaolin Yang Liang Xu Jesse thé Zhongchao Tan Hesheng Yu Key Laboratory of Coal Processing and Efficient Utilization of Ministry of Education School of Chemical Engineering and TechnologyChina University of Mining and TechnologyXuzhouJiangsu 221116China Department of Mechanical&Mechatronics Engineering University of Waterloo200 University Avenue WestWaterlooOntario N2L 3G1Canada Lakes Environmental Research Inc. 170 Columbia St.W.Suite 1WaterlooOntarioN2L 3L3 Canada Eastern Institute for Advanced Study Eastern Institute of TechnologyNingboZhejiang 315200China Department of Energy and Power Engineering Tsinghua UniversityBeijing 100084China

Coal-gangue object detection has attracted substantial attention because it is the core of realizing vision-based intelligent and green coal separation. However, most existing studies have been focused on laboratory datasets and prioritized model lightweight. this makes the coal-gangue object detection challenging to adapt to the complex and harsh scenes of real production environments. therefore, our project collected and labeled image datasets of coal and gangue under real production conditions from a coal preparation plant. We then designed a one-stage object model, named STATNet, following the “backbone-neck-head” architecture with the aim of enhancing the detection accuracy under industrial coal preparation scenarios. the proposed model utilizes Swin Transformer as backbone module to extract multi-scale features, improved path augmentation feature pyramid network (iPAFPN) as neck module to enrich feature fusion, and task-aligned head (TAH) as head module to mitigate conflicts and misalignments between classification and localization tasks. Experimental results on a real-world industrial dataset demonstrate that the proposed STATNet model achieves an impressive AP50 of 89.27 %, significantly surpassing several state-of-the-art baseline models by 2.02 % to 5.58 %. Additionally, it exhibits stronger robustness in resisting image corruption and perturbation. these findings demonstrate its promising prospects in practical coal and gangue separation applications.

关键词： Coal-gangue detection Swin transformer Impr oved path augmentation feature pyranid network Task-aligned head Object detection