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impacts of land uses on runoff and soil erosion A case study in Hilkot watershed Pakistan

international Journal of sediment Research 2011年第3期26卷 343-352页

作者： ZOKAiB s. NAsER Gh. school of Engineering University of British Columbia-OkanaganCanada

in certain areas of the Hindu Kush-Himalayas（HKH）,ecological situation is depleting day by day and approaching to the point of no return through gradual environmental *** soil erosion from most of the areas is a serious threat to sustainable agriculture and sediment accumulation in down stream *** extensive study in the Hilkot watershed,a catchment of Terbala Dam, was started by the People and Resource Dynamics Project in *** objectives of this study were to calculate annual runoff and soil losses from different land uses and compare their seasonal distribution at plot *** experimental plots based on land use classification（***, forests,agricultural,and pasture lands）were *** falls in the monsoon region,about 38% rainfall occurred in the monsoon period（July to september）,while in the pre-monsoon（March to June）and the winter period（October to February）received 35%and 27%of the total rainfall, *** annual rainfall in the watershed was 1160 *** runoff and soil loss pattern varied among different land use *** all the erosion plots,almost 50%of the runoff and soil loss occurred during the monsoon period and was negligible during *** mean maximum runoff was from the degraded plot（674 m;/ha/y）,while minimum was observed from the pasture plot（310 m;/ha/y）.Average runoffs on other land uses were 529 and 460 m;/ha/y,from the forest and agriculture plots,*** soil loss from all land uses ranged between 0.3 to 16.3 t/ha. Average maximum soil loss was recorded from the degraded plot（6.5 t/ha/y）and average minimum （1.8 t/ha/y）was on the pasture ***,average soil from other plots was 3.3 and 3.4 t/ha/y, measured from the forest and agricultural plots,respectively.

关键词： Runoff soil loss Land use seasonal distribution Hindu Kush-Himalayan region

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Human stress Recognition by Correlating Vision and EEG Data

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Computer systems science & Engineering 2023年第6期45卷 2417-2433页

作者： s.Praveenkumar T.Karthick sRM institute of science and Technology Department of Data Science and Business SystemsSchool of ComputingKattankulathur603203TamilnaduIndia

Because stress has such a powerful impact on human health,we must be able to identify it automatically in our everyday *** human activity recognition(HAR)system use data from several kinds of sensors to try to recognize and evaluate human actions automatically recognize and evaluate human *** the multimodal dataset DEAP(Database for Emotion Analysis using Physiological signals),this paper presents deep learning(DL)technique for effectively detecting human *** combination of vision-based and sensor-based approaches for recognizing human stress will help us achieve the increased efficiency of current stress recognition systems and predict probable actions in advance of when *** on visual and EEG(Electroencephalogram)data,this research aims to enhance the performance and extract the dominating characteristics of stress *** the stress identification test,we utilized the DEAP dataset,which included video and EEG *** also demonstrate that combining video and EEG characteristics may increase overall performance,with the suggested stochastic features providing the most accurate *** the first step,CNN(Convolutional Neural Network)extracts feature vectors from video frames and EEG *** Level(FL)fusion that combines the features extracted from video and EEG *** use XGBoost as our classifier model to predict stress,and we put it into *** stress recognition accuracy of the proposed method is compared to existing methods of Decision Tree(DT),Random Forest(RF),AdaBoost,Linear Discriminant Analysis(LDA),and KNearest Neighborhood(KNN).When we compared our technique to existing state-of-the-art approaches,we found that the suggested DL methodology combining multimodal and heterogeneous inputs may improve stress identification.

关键词： Mental stress physiological data XGBoost feature fusion DEAP video data EEG CNN HAR

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Metaheuristics with Vector Quantization Enabled Codebook Compression Model for secure industrial Embedded Environment

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intelligent Automation & soft Computing 2023年第6期36卷 3607-3620页

作者： Adepu shravan Kumar s.srinivasan Department of Biomedical Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesSaveetha UniversitySaveetha NagarThandalamChennai602105India

At the present time,the industrial internet of Things(iioT)has swiftly evolved and emerged,and picture data that is collected by terminal devices or ioT nodes are tied to the user's private *** use of image sensors as an automa-tion tool for the iioT is increasingly becoming more *** to the fact that this organisation transfers an enormous number of photographs at any one time,one of the most significant issues that it has is reducing the total quantity of data that is sent and,as a result,the available bandwidth,without compromising the image *** compression in the sensor,on the other hand,expedites the transfer of data while simultaneously reducing bandwidth *** traditional method of protecting sensitive data is rendered less effective in an environment dominated by ioT owing to the involvement of third *** image encryp-tion model provides a safe and adaptable method to protect the confidentiality of picture transformation and storage inside an iioT *** helps to ensure that image datasets are kept *** Linde–Buzo–Gray(LBG)methodology is an example of a vector quantization algorithm that is extensively used and a rela-tively new form of picture reduction known as vector quantization(VQ).As a result,the purpose of this research is to create an artificial humming bird optimi-zation approach that combines LBG-enabled codebook creation and encryption(AHBO-LBGCCE)for use in an iioT *** the beginning,the AHBO-LBGCCE method used the LBG model in conjunction with the AHBO algorithm in order to construct the *** Burrows-Wheeler Transform(BWT)model is used in order to accomplish codebook *** addition,the Blowfish algorithm is used in order to carry out the encryption procedure so that security may be attained.A comprehensive experimental investigation is carried out in order to verify the effectiveness of the proposed algorithm in comparison to other *** experimental values ensure that the suggeste

关键词： Codebook compression industrial internet of things lbg model metaheuristics vector quantization

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Role of frequency band integration in sharpening frequency tunings of the inferior colliculus neurons in the big brown bat, Eptesicus fuscus

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Chinese science Bulletin 2004年第10期49卷 1026-1031页

作者： WUFeijian CHENQicai JENPhilipH.s. sHENJunxian schoolofLifesciences.CentralChinaNormalUniversity.Wuhan430079.China DivisionofBiologicalsciences UniversityofMissouri-Columbia.MO65211.USA LaboratoryofVisualinformationProcessing InstituteofBiophysicsChineseAcademyofSciencesBeijing100101China

By means of a particular two-tone stimulationparadigm in combination of using a pair of electrodes forsimultaneously recording from two inferior colliculus (iC)neurons, the current in vivo study is undertaken to explorethe role of frequency band integration (FBi) in sharpening offrequency tuning in the big brown bat, Eptesicus *** major results are found: (1) The paired neurons cor-related to FBi are located not only within the same frequencyfilter bandwidth (FFB), but also across different FFBs. Therelations of their frequency tuning curves (FTCs) are mainlyof two types: the flank-overlapped and overlaid patterns. (2)Although the sharpness of FTCs between paired neurons ismutual, the sharpening efficiency of neurons located withinthe same FFB is higher than that of neurons across FFBs,and the FTCs of neurons with the best frequencies (BF) of 20--30 kHz are most strongly sharpened. (3) The strength ofFBi is weak near the BF but gradually increased with fre-quencies away from the BF of sound stimuli. This suggeststhat the dynamical FBi of the iC neurons located within and across the FFBs might be involved in the formation of func-tional FFB structures.

关键词：频带综合频率调节下丘神经蝙蝠平滑

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Predictive-Analysis-based Machine Learning Model for Fraud Detection with Boosting Classifiers

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Computer systems science & Engineering 2023年第4期45卷 231-245页

作者： M.Valavan s.Rita Department of statistics Periyar UniversitySalemTamilnaduIndia

Fraud detection for credit/debit card,loan defaulters and similar types is achievable with the assistance of Machine Learning(ML)algorithms as they are well capable of learning from previous fraud trends or historical data and spot them in current or future *** cases are scant in the comparison of non-fraudulent observations,almost in all the *** such cases detecting fraudulent transaction are quite *** most effective way to prevent loan default is to identify non-performing loans as soon as *** learning algorithms are coming into sight as adept at handling such data with enough computing *** this paper,the rendering of different machine learning algorithms such as Decision Tree,Random Forest,linear regression,and Gradient Boosting method are compared for detection and prediction of fraud cases using loan fraudulent *** model accuracy metric have been performed with confusion matrix and calculation of accuracy,precision,recall and F-1 score along with Receiver Operating Characteristic(ROC)curves.

关键词： Random forest decision tree logistic regression machine Learning gradient boosting method confusion matrix

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Hash-indexing Block-Based Deduplication Algorithm for Reducing storage in the Cloud

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Computer systems science & Engineering 2023年第7期46卷 27-42页

作者： D.Viji s.Revathy Department of Computer science and Engineering Sathyabama Institute of Science and TechnologyChennaiIndia

Cloud storage is essential for managing user data to store and retrieve from the distributed data *** storage service is distributed as pay a service for accessing the size to collect the *** to the massive amount of data stored in the data centre containing similar information and file structures remaining in multi-copy,duplication leads to increase storage *** potential deduplication system doesn’t make efficient data reduction because of inaccuracy in finding similar data *** creates a complex nature to increase the storage consumption under *** resolve this problem,this paper proposes an efficient storage reduction called Hash-indexing Block-based Deduplication(HiBD)based on segmented Bind Linkage(sBL)Methods for reducing storage in a cloud ***,preprocessing is done using the sparse augmentation ***,the preprocessed files are segmented into blocks to make *** block of the contents is compared with other files through semantic Content source Deduplication(sCsD),which identifies the similar content presence between the *** on the content presence count,the Distance Vector Weightage Correlation(DVWC)estimates the document similarity weight,and related files are grouped into a ***,the segmented bind linkage compares the document to find duplicate content in the cluster using similarity weight based on the coefficient match *** implementation helps identify the data redundancy efficiently and reduces the service cost in distributed cloud storage.

关键词： Cloud computing deduplication hash indexing relational content analysis document clustering cloud storage record linkage

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BHLM:Bayesian theory-based hybrid learning model for multi-document summarization

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international Journal of Modeling, simulation, and scientific Computing 2018年第2期9卷 229-250页

作者： s.suneetha A.Venugopal Reddy Computer science and Engineering Department Hasvita institute of Engineering and Technology Hyderabad India Jawaharlal Nehru Technological University Hyderabad India

in order to understand and organize the document in an efficient way,the multidocument summarization becomes the prominent technique in the internet *** the information available is in a large amount,it is necessary to summarize the document for obtaining the condensed *** perform the multi-document summarization,a new Bayesian theory-based Hybrid Learning Model(BHLM)is proposed in this ***,the input documents are preprocessed,where the stop words are removed from the ***,the feature of the sentence is extracted to determine the sentence score for summarizing the *** extracted feature is then fed into the hybrid learning model for ***,learning feature,training error and correlation coefficient are integrated with the Bayesian model to develop ***,the proposed method is used to assign the class label assisted by the mean,variance and probability ***,based on the class label,the sentences are sorted out to generate the final summary of the *** experimental results are validated in MATLAB,and the performance is analyzed using the metrics,precision,recall,F-measure and *** proposed model attains 99.6%precision and 75%rouge-1 measure,which shows that the model can provide the final summary efficiently.

关键词： Multi-document text feature sentence score hybrid learning model Bayesian theory

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implementation of Hybrid Particle swarm Optimization for Optimized Regression Testing

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intelligent Automation & soft Computing 2023年第6期36卷 2575-2590页

作者： V.Prakash s.Gopalakrishnan sAsTRA Deemed University KumbakonamTamilnadu613401India

software test case optimization improves the efficiency of the software by proper structure and reduces the fault in the *** existing research applies various optimization methods such as Genetic Algorithm,Crow search Algorithm,Ant Colony Optimization,etc.,for test case *** existing methods have limitations of lower efficiency in fault diagnosis,higher computa-tional time,and high memory *** existing methods have lower effi-ciency in software test case optimization when the number of test cases is *** research proposes the Tournament Winner Genetic Algorithm(TW-GA)method to improve the efficiency of software test case *** information system(His)software was used to evaluate TW-GA model perfor-mance in test case *** tournament Winner in the proposed method selects the instances with the best fitness values and increases the exploitation of the search to find the optimal *** TW-GA method has higher exploita-tion that helps to find the mutant and equivalent mutation that significantly increases fault diagnosis in the *** TW-GA method discards the infor-mation with a lower fitness value that reduces the computational time and mem-ory *** TW-GA method requires 5.47 s and the MOCsFO method requires 30 s for software test case optimization.

关键词： Equivalent mutation fault diagnosis hospital information system software test case optimization tournament winner genetic algorithm

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implementation of FPGA Based MPPT Techniques for Grid-Connected PV system

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intelligent Automation & soft Computing 2023年第2期35卷 1783-1798页

作者： Thamatapu Eswara Rao s.Elango Department of Electrical and Electronics Engineering Coimbatore Institute of TechnologyCoimbatoreIndia

Global energy demand is growing rapidly owing to industrial growth and *** energy sources are driven by limited reserves and rapid depletion of conventional energy sources(e.g.,fossil fuels).solar photovol-taic(PV),as a source of electricity,has grown in popularity over the last few dec-ades because of their clean,noise-free,low-maintenance,and abundant availability of solar *** are two types of maximum power point track-ing(MPPT)techniques:classical and evolutionary algorithm-based *** and less complex perturb and observe(P&O)and incremental conduc-tance(iNC)approaches are extensively employed among classical *** study used aﬁeld-programmable gate array(FPGA)-based hardware arrange-ment for a grid-connected photovoltaic(PV)*** PV panels,MPPT con-trollers,and battery management systems are all components of the proposed *** the developed hardware prototype,various modes of operation of the grid-connected PV system were examined using P&O and incremental con-ductance MPPT approaches.

关键词： Grid connected PV system perturb and observe(P&O) incremental MPPT boost converter battery

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First sHRiMP zircon U-Pb ages for Hutuo Group in Wutaishan:Further evidence for Palaeoproterozoic amalgamation of North China Craton

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Chinese science Bulletin 2004年第1期49卷 83-90页

作者： s.A.Wilde ZHAOGuochun WANGKaiyi sUNMin DepartmentofAppliedGeology CurtinUniversityofTechnologyPOBoxU1987Perth6845Australia DepartmentofEarthscience UniversityofHongKongPokfulamRoadHongKongChina instituteofGeologyandGeophysics ChineseAcademyofSciencesBeijing100029China

A felsic tuffaceous rock, obtained from a metamorphosed sequence of volcanics and sediments of the Hutuo Group, 8 km south of Taihuai in Wutaishan, contains two zircon populations. These record sHRiMP ^207Pb/^206Pb weighted mean ages of 2180 ± 5 Ma and 2087 ± 9 Ma, respectively. The older date is within error of the age of the Dawaliang Granite in Wutaishan and is considered to be derived from a similar crustal magmatic source. The younger date is within error of reported ages from metasediments and meta-volcanics of the Wanzi supracrustal rocks and the Nanying granitic gneisses in the adjacent Fuping Complex and is interpreted to be the age of volcanism in the Hutuo Group. These data establish that: (1) the Hutuo Group is Paleoproterozoic and not Archean in age and (2) the volcanism and sedimentation were coeval in the Wutai and Fuping complexes. sedimentation was therefore widespread at this time and possibly reflects deposition along an evolving continental margin, most likely the western margin of the Eastern Block of the North China Craton. The age of 2087±9 Ma for volcanism in the Hutuo Group means that it must have been deformed and metamorphosed after this *** further supports the evidence, obtained from other recent studies, that the main tectonism in the Wutaishan areaoccurred at ～1.8 Ga during the Lüliang orogeny. This orogeny resulted in the collision of the Eastern and Western blocks of the North China Craton and formed part of a global supercontinental amalgamation event.

关键词：锆石五台山元古代山西稳定地块

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