2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence最新文献

Hydrological Modelling to Inform Forest Management: Moving Beyond Equivalent Clearcut Area 水文建模为森林管理提供信息:超越同等砍伐面积

2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence Pub Date : 2023-09-28 DOI: 10.22230/jwsm.2023v6n1a47

Matthew Chernos, Kim Green, Ryan MacDonald

{"title":"Hydrological Modelling to Inform Forest Management: Moving Beyond Equivalent Clearcut Area","authors":"Matthew Chernos, Kim Green, Ryan MacDonald","doi":"10.22230/jwsm.2023v6n1a47","DOIUrl":"https://doi.org/10.22230/jwsm.2023v6n1a47","url":null,"abstract":"Forest disturbance can alter the hydrologic conditions of a watershed, including the frequency, magnitude, and timing of peak and low flows. Equivalent Clearcut Area (ECA) has been routinely used in watershed assessments to estimate hydrologic alteration due to forest disturbance. ECA analyses typically rely on broad regional assumptions, qualitative observations, and/or expert judgement, making it difficult to provide accurate quantitative estimates of hydrologic change. Process-based hydrological models offer an improved approach since they replicate watershed processes, can simulate land cover and climate change scenarios, and provide quantitative estimates of hydrologic change, including at ungauged points of interest. A workflow using a regionally calibrated hydrological model to investigate forest disturbance and future climate change scenarios is demonstrated. Results are contrasted with ECA-based outputs and emphasize that in addition to the amount of forest disturbance, watershed physical characteristics and the location of disturbance within a watershed influence the hydrologic response. This approach provides forest managers with quantitative outputs that support risk-based forest management decisions and presents a substantial improvement over ECA-based methods. Keywords: hydrological modelling, ECA-based analysis, watershed assessment, forest disturbance, cumulative effects, risk-based forest management","PeriodicalId":6651,"journal":{"name":"2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135425171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhanced feature mining and classifier models to predict customer churn for an E-retailer 增强的特征挖掘和分类器模型预测电子零售商的客户流失

2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence Pub Date : 2017-10-30 DOI: 10.1201/B21822-13

K. B. Subramanya, Arun Kumar Somani

{"title":"Enhanced feature mining and classifier models to predict customer churn for an E-retailer","authors":"K. B. Subramanya, Arun Kumar Somani","doi":"10.1201/B21822-13","DOIUrl":"https://doi.org/10.1201/B21822-13","url":null,"abstract":"Customer Churn, an event indicating a customer abandoning an established relation with a business is an important problem researched well, both for academic and commercial interest. Through this work, we propose an improved churn prediction model that emphasizes on an effective data collection pipeline through varied channels capturing explicit and implicit customer footprints. The goal of this paper is to demonstrate the improvement in classifier efficiency using an extended feature set and feature selection algorithms. Prominent features playing a vital role in customer churn are also ranked. The contributions through this paper can be broadly categorized into 3 folds: First, we discuss how popular data mining tools in Hadoop stack help extract several implicit customer interaction metrics including Sales and Clickstream logs generated as a result of customer interaction. Second, through Feature Engineering techniques we verify that some of the new features we propose have a definite impact on customer churn. Finally, we demonstrate how Regularized Logistic Regression, SVM and Gradient Boost Random Forests are the best performing models for predicting customer churn verified through comprehensive cross-validation techniques.","PeriodicalId":6651,"journal":{"name":"2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence","volume":"107 1","pages":"531-536"},"PeriodicalIF":0.0,"publicationDate":"2017-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73479404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

Towards the practical design of performance-aware resilient wireless NoC architectures 面向性能感知弹性无线NoC架构的实用设计

2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence Pub Date : 2017-06-07 DOI: 10.1109/CONFLUENCE.2017.7943199

Michael Opoku Agyeman, W. Zong, T. Kanakis, K. Tong, T. Mak

{"title":"Towards the practical design of performance-aware resilient wireless NoC architectures","authors":"Michael Opoku Agyeman, W. Zong, T. Kanakis, K. Tong, T. Mak","doi":"10.1109/CONFLUENCE.2017.7943199","DOIUrl":"https://doi.org/10.1109/CONFLUENCE.2017.7943199","url":null,"abstract":"Recently, an improved surface wave-enabled communication fabric has been proposed to solve the reliability issues of emerging hybrid wired-wireless Network-on-Chip (WiNoC) architectures. Thus, providing a promising solution to the performance and scalability demands of the fast-paced technological growth towards exascale and Big-Data processing on future System-on-Chip (SoC) design. However, WiNoCs tradeoff optimized performance for cost by restricting the number of area and power hungry wireless nodes. Consequently, in this paper, we propose a low-latency adaptive router with a low-complexity single-cycle bypassing mechanism to alleviate the performance degradation due to the slow wired routers in such emerging hybrid NoCs. The proposed router is able to redistribute traffic in the network to alleviate average packet latency at both low and high traffic conditions. As a second contribution the paper presents an experimental evaluation of a practically implemented surface wave communication fabric. By reducing the latency between the wired nodes and wireless nodes the proposed router can improve performance efficiency in terms of average packet delay by an average of 50% in WiNoCs.","PeriodicalId":6651,"journal":{"name":"2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence","volume":"15 1","pages":"479-484"},"PeriodicalIF":0.0,"publicationDate":"2017-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81114870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Adaptive virtual MIMO single cluster optimization in a small cell 小小区自适应虚拟MIMO单簇优化

2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence Pub Date : 2017-01-13 DOI: 10.1109/CONFLUENCE.2017.7943198

T. Kanakis, Michael Opoku Agyeman, Anastasios G. Bakaoukas

引用次数: 2

Queueing approach based MANET performance analysis 基于排队方法的MANET性能分析

2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence Pub Date : 2017-01-01 DOI: 10.1109/CONFLUENCE.2017.7943187

Dr. Aleem Ali, Neeta Singh

引用次数: 2

Study of optimization methods for tuning of PID gains for three link manipulator 三连杆机械臂PID增益整定的优化方法研究

2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence Pub Date : 2017-01-01 DOI: 10.1109/CONFLUENCE.2017.7943131

Tribhi Kathuria, Ayush Gupta, J. Kumar, Vineet Kumar, K. Rana

{"title":"Study of optimization methods for tuning of PID gains for three link manipulator","authors":"Tribhi Kathuria, Ayush Gupta, J. Kumar, Vineet Kumar, K. Rana","doi":"10.1109/CONFLUENCE.2017.7943131","DOIUrl":"https://doi.org/10.1109/CONFLUENCE.2017.7943131","url":null,"abstract":"Robotic manipulators are used in wide range of industrial applications. These are highly complex, multi-input multi-output and coupled systems requiring efficient control mechanism. This complexity is further enhanced as the number of links is increased. PID control is the most widely employed control scheme in the manufacturing industry but conventional tuning approaches for tuning PID gains do not offer satisfactory results for complex systems like robotic manipulators. This generates the need for advance optimization techniques to carry out the tuning of PID controller for a customized performance index. This paper presents a comparative study of the performances of three such heuristic optimization algorithms, namely. Teacher Learning Based Optimization Algorithm (TLBO), Flower Pollination Optimization Algorithm (FPO) and Genetic Algorithm (GA) for tuning the PID controllers applied to a three link planar rigid robotic manipulator. The trajectory tracking and disturbance rejection performances of the PID controller tuned by these algorithms are considered. The tuning has been done by minimizing the weighted sum of integral absolute error and integral of absolute controller output for path following. Based on the results obtained, it was concluded that TLBO offers superior results.","PeriodicalId":6651,"journal":{"name":"2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence","volume":"12 1","pages":"99-104"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85958401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Performance of image fusion technique using 4×4 block wavelet cosine transformation 利用4×4块小波余弦变换实现图像融合

2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence Pub Date : 2017-01-01 DOI: 10.1109/CONFLUENCE.2017.7943226

Blessy Chacko, S. Agrwal, S. Gupta, Harendra Chahar, Saurabh R. Srivastava, N. Srivastav

{"title":"Performance of image fusion technique using 4×4 block wavelet cosine transformation","authors":"Blessy Chacko, S. Agrwal, S. Gupta, Harendra Chahar, Saurabh R. Srivastava, N. Srivastav","doi":"10.1109/CONFLUENCE.2017.7943226","DOIUrl":"https://doi.org/10.1109/CONFLUENCE.2017.7943226","url":null,"abstract":"Image fusion is the process for combining the characteristics of two or more images into an image file to generate more information into an image. Research Issues of Image fusion is enhancement of visual quality of fused image by reducing the noise. Wavelet transformation based Image fusion techniques provide better robustness for statistical attacks in comparison to Discrete Cosine Transform domain and Spatial Domain-based Image fusion. The combined technique of discrete cosine harmonic wavelet transform (DCHWT) provides advantages of DWT and DCT both techniques but the DWT have the disadvantage of fraction loss in embedding which increases mean square error and results decreasing PSNR. Robustness of fusion technique is proportional to PSNR. The Proposed algorithm presents Hybrid Integer wavelet transform and 4×4 block discrete cosine transform based image fusion technique to obtain image quality and higher informatics compared to DWT-DCT and DCHWT based fusion technique. The proposed combined 4×4 block IWT-DCT based image fusion technique reduces the MSE compared to existing DWT-DCT and DCHWT based image fusion.","PeriodicalId":6651,"journal":{"name":"2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence","volume":"15 1","pages":"618-622"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77049470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Logic of digital competition: A framework for impact of digital architecture on firm performance in software based ecosystems 数字竞争的逻辑:基于软件的生态系统中数字架构对企业绩效影响的框架

2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence Pub Date : 2017-01-01 DOI: 10.1109/CONFLUENCE.2017.7943242

Chetan Juneja, R. S. Rai, H. Kothari

{"title":"Logic of digital competition: A framework for impact of digital architecture on firm performance in software based ecosystems","authors":"Chetan Juneja, R. S. Rai, H. Kothari","doi":"10.1109/CONFLUENCE.2017.7943242","DOIUrl":"https://doi.org/10.1109/CONFLUENCE.2017.7943242","url":null,"abstract":"Pervasive and networked use of digital technologies has disrupted business strategies, industry structure and emergence of newer organizational forms with firms increasingly competing as software based ecosystems increasingly driven by convergence, changing materiality relationship between form and function of products and inter firm relationships. Decomposition of digital ecosystems into core and complementary module can potentially enable combinatorial innovation and asymmetric business models of platform providers and complementors. The layered modular architecture of digital artifacts, modularity and generativity of the ecosystem architecture help the evolutionary changes to the ecosystem through voluntaristic innovation by heterogeneous contributors which is a critical driver of ecosystem success. In this study using multi-theoretic lens of resource based view, platform architecture, strategic logic of opportunity and strategy as practice we develop a nomological network to explore the impact of platform architecture on complementor firm performance and posit a mediating role of firm's dynamic capabilities enabling competitive action.","PeriodicalId":6651,"journal":{"name":"2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence","volume":"17 1","pages":"702-707"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83002355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Designing optimal architecture of neural network with particle swarm optimization techniques specifically for educational dataset 应用粒子群优化技术设计面向教育数据集的神经网络最优结构

2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence Pub Date : 2017-01-01 DOI: 10.1109/CONFLUENCE.2017.7943123

Devika Chhachhiya, Amita Sharma, Manish Gupta

{"title":"Designing optimal architecture of neural network with particle swarm optimization techniques specifically for educational dataset","authors":"Devika Chhachhiya, Amita Sharma, Manish Gupta","doi":"10.1109/CONFLUENCE.2017.7943123","DOIUrl":"https://doi.org/10.1109/CONFLUENCE.2017.7943123","url":null,"abstract":"Designing an optimal Neural Network architecture plays an important role in the performance of a neural network model. In the past few years, various bio-inspired optimization techniques have been applied to find the optimal architecture of a neural network model. In this paper Particle Swarm Optimization (PSO) technique has been applied with back propagation algorithm to find an optimal architecture for feed forward Neural Network. To optimize the architecture of neural network model Parameters considered are hidden neurons, learning rate and activation function. Fitness function applied for the selection of the optimal combination of the parameters is root mean square error (RMSE). Due to privatization of education number of private institutes and universities are increasing rapidly every year. This increase has resulted in huge number of data (NAAC reports) regarding the assessment and accreditation of higher education institutions. Dataset of 380 educational institutes has been collected from the official site of National Assessment and Accreditation Council (NAAC). Hybrid of PSO with back propagation has been applied on this dataset. Results obtained from both of the algorithms are compared on the basis of the fitness function and accuracy obtained.","PeriodicalId":6651,"journal":{"name":"2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence","volume":"76 1","pages":"52-57"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86457212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 14

The detailed experimental analysis of bucket sort 对斗式排序进行了详细的实验分析

2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence Pub Date : 2017-01-01 DOI: 10.1109/CONFLUENCE.2017.7943114

Neetu Faujdar, Shipra Saraswat

引用次数: 6