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International Conference on Emerging Technologies in Data Mining and Information Security, IEMIS 2018

作者： Ghosh, Sirshendu Sekhar Patra, Moujhuri Jain, Aruna Department of Computer Applications National Institute of Technology JamshedpurJharkhand831014 India Department of Master of Computer Applications Netaji Subhash Engineering College Garia Kolkata700152 India Department of Computer Science & Engineering Birla Institute of Technology Mesra RanchiJharkhand835215 India

ISBN: (纸本)9789811315008

Present Web infrastructure is severely suffering from heavy congestion and enormous traffic burden upon the widely distributed client network around the globe due to proliferating growth in terms of overpopulated users along with day-by-day addition of latest complex and resource hungry Web applications, tools, and services. This leads to continuous increase in Web access delay (latency) faced by the users challenging the unprecedented popularity of the World Wide Web (WWW). Proxy caching is a renowned and current strategy for refining the distributed Web-based system performance particularly applicable for remote areas which severely suffers from poor network communication and limited bandwidth availability. Web prefetching is another very useful strategy which prefetches and keeps the closely related Web objects to be accessed by the users’ in future into cache, based on their interest pattern. But still, there is a significant performance gap between the users’ requests and the result provided. The intelligent and sophisticated integration of these two strategies along with one more performance enhancement technique, i.e., Web log mining, can provide an excellent and most successful solution to minimize the problem of latency and improve the overall Web quality of service. This paper provides an Integrated Proxy Prefetch-Cache System framework with the above benefits to satisfy maximum clients’ requests with improved response time as well as with minimum latency. Also, the framework has been successfully incorporated into the highly scalable, hierarchical as well as distributed geographical region-based proxy server clusters with enhanced content co-operation, efficient metadata management, and low access delay. Using real-time Web proxy server network deployment with online trace-driven results analysis, the current framework guarantees improved object consistency between clustered proxy server caches and original Web servers. © Springer Nature Singapore Pte Ltd

关键词： Metadata

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*** as digital platform for vegetation analysis and estimation of carbon stock in KEHATI aqua park

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AIP Conference Proceedings 2024年第1期3026卷

作者： Nanda Satya Nugraha Dian Pratama Putra Mohammad Prasanto Bimantio Amallia Ferhat Rama Zakaria Rudi Nirwantono Teddy Suparyanto Bens Pardamean Faculty of Forestry Institute of Agriculture STIPER Yogyakarta Indonesia 55282 Faculty of Agriculture Institute of Agriculture STIPER Yogyakarta Indonesia 55282 Faculty of Agricultural Technology Institute of Agriculture STIPER Yogyakarta Indonesia 55282 PT. Tirta Investama Pabrik Klaten Klaten Central Java Indonesia 57474 Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 1148 Biotechnology Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

KEHATI AQUA Park is one of the green areas managed by PT. Tirta Investama Klaten (Klaten Factory). This area is located in Wangen and Ponggok Villages, Polanharjo District, Klaten Regency, Central Java, and is an integral part of the company’s seriousness in carbon reduction movement. When maintenance of the area is important for the sustainability of the park, there is however no data on the trees inventory in the area. Therefore, this study aims to invent the trees at KEHATI AQUA Park and evaluate the potential of the area to become a carbon sink using *** application. This study was conducted at the KEHATI AQUA Park. The census method was performed to collect tree data, and the result was recorded in *** application. The carbon stock calculation was estimated using the application according to the tree data submitted in the application. The study included a total of 1048 plantation spots in 51 tree species. From those numbers, about 738 trees existed, and the remaining spots were blank spaces. Based on the condition of the trees, those were 660 good trees, 17 dry trees, and 61 under pest infection. The carbon stock estimation at KEHATI AQUA Park Klaten in the next five years (2026) is around 40 tons of carbon. Therefore, it can be concluded that the park is valuable as an area to preserve biodiversity and as a carbon sink.

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Android-Based oil palm farmer’s income analysis to support precision agriculture

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AIP Conference Proceedings 2023年第1期2594卷

作者： M. P. Bimantio A. Ferhat L. Isnaini D. P. Putra T. Suparyanto B. Pardamean Department of Food and Agricultural Technology Institute of Agriculture STIPER Yogyakarta Indonesia 55281 Department of Agricultural Socio-Economics Institute of Agriculture STIPER Yogyakarta Indonesia 55281 Department of Agricultural Socio-Economics Gadjah Mada University Yogyakarta Indonesia 55281 Department of Agrotechnology Institute of Agriculture STIPER Yogyakarta Indonesia 55281 Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480

The purpose of this research is to create a simulator application in calculating farmer's income from the sale of fresh fruit bunches. Farmers can easily find out the outcomes based on how many kilograms of crops are sold through this application. This research was conducted in Mesuji Regency, Lampung Province, using primary data and descriptive analysis. The sampling technique utilized a proportional random sampling method and consisted of 88 oil palm farmers. The results indicated that the application made it simpler for farmers to find out their income. Farmers only needed to input the land area, the harvest number obtained on the harvest day that had been carried out, and the price of fresh fruit bunches so that they would know the estimated monthly and annual income calculations. These calculations can be used by farmers as a predicting and planning tool to avoid losses.

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The role of input imaging combination and ADC threshold on segmentation of acute ischemic stroke lesion using U-Net

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European Radiology 2023年第9期33卷 6157-6167页

作者： Li, Ya-Hui Lin, Shao-Chieh Chung, Hsiao-Wen Chang, Chia-Ching Peng, Hsu-Hsia Huang, Teng-Yi Shen, Wu-Chung Tsai, Chon-Haw Lo, Yu-Chien Lee, Tung-Yang Juan, Cheng-Hsuan Juan, Cheng-En Chang, Hing-Chiu Liu, Yi-Jui Juan, Chun-Jung Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Department of Medical Imaging China Medical University Hsinchu Hospital No. 199 Sec. 1 Xinglong Rd. Zhubei City Hsinchu County 302 Hsinchu Taiwan Ph.D. Program in Electrical and Communication Engineering Feng Chia University Taichung Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan Department of Management Science National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Biomedical Engineering and Environmental Sciences National Tsing Hua University Hsinchu Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Radiology School of Medicine College of Medicine China Medical University Taichung Taiwan Department of Medical Imaging Medical University Hospital Taichung Taiwan Department of Neurology China Medical University Hospital Taichung Taiwan Cheng Ching Hospital Taichung Taiwan Master’s Program of Biomedical Informatics and Biomedical Engineering Feng Chia University Taichung Taiwan Department of Automatic Control Engineering Feng Chia University No. 100 Wenhwa Rd. Seatwen Taichung 40724 Taiwan Department of Biomedical Engineering The Chinese University of Hong Kong ERB1112 11/F William M.W. Mong Engineering Building N.T Shatin Hong Kong Multi-Scale Medical Robotics Center The Chinese University of Hong Kong N.T Shatin Hong Kong Department of Biomedical Engineering National Defense Medical Center Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan

Background: To evaluate the effect of the weighting of input imaging combo and ADC threshold on the performance of the U-Net and to find an optimized input imaging combo and ADC threshold in segmenting acute ischemic stroke (AIS) lesion. Methods: This study retrospectively enrolled a total of 212 patients having AIS. Four combos, including ADC-ADC-ADC (AAA), DWI-ADC-ADC (DAA), DWI-DWI-ADC (DDA), and DWI-DWI-DWI (DDD), were used as input images, respectively. Three ADC thresholds including 0.6, 0.8 and 1.8 × 10^–3 mm²/s were applied. Dice similarity coefficient (DSC) was used to evaluate the segmentation performance of U-Nets. Nonparametric Kruskal–Wallis test with Tukey–Kramer post-hoc tests were used for comparison. A p <.05 was considered statistically significant. Results: The DSC significantly varied among different combos of images and different ADC thresholds. Hybrid U-Nets outperformed uniform U-Nets at ADC thresholds of 0.6 × 10^–3 mm²/s and 0.8 × 10^–3 mm²/s (p <.001). The U-Net with imaging combo of DDD had segmentation performance similar to hybrid U-Nets at an ADC threshold of 1.8 × 10^–3 mm²/s (p =.062 to 1). The U-Net using the imaging combo of DAA at the ADC threshold of 0.6 × 10^–3 mm²/s achieved the highest DSC in the segmentation of AIS lesion. Conclusions: The segmentation performance of U-Net for AIS varies among the input imaging combos and ADC thresholds. The U-Net is optimized by choosing the imaging combo of DAA at an ADC threshold of 0.6 × 10^–3 mm²/s in segmentating AIS lesion with highest DSC. Key Points: • Segmentation performance of U-Net for AIS differs among input imaging combos. • Segmentation performance of U-Net for AIS differs among ADC thresholds. • U-Net is optimized using DAA with ADC = 0.6 × 10^–3mm²/s. © 2023, The Author(s), under exclusive licence to European Society of Radiology.

关键词： Deep Learning Diffusion Magnetic Resonance Imaging Ischemic Stroke Neural Networks, computer Retrospective Study

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Grain Boundary Detection and Phase Segmentation of SEM Ferrite–Pearlite Microstructure Using SLIC and Skeletonization

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Journal of The Institution of Engineers (India): Series D 2019年第2期100卷 203-210页

作者： Gupta, Subir Sarkar, Jit Banerjee, Abhijit Bandyopadhyay, N.R. Ganguly, Subhas School of Materials Science and Engineering Indian Institute of Engineering Science and Technology Shibpur HowrahWest Bengal711103 India Deparment of Master of Computer Application B C Roy Engineering College DurgapurWest Bengal713206 India Boldink Technologies Private Limited HowrahWest Bengal711110 India Deparment of Electronics and Communication Engineering B C Roy Engineering College DurgapurWest Bengal713206 India Department of Metallurgical Engineering National Institute of Technology Raipur RaipurChhattisgarh492010 India

In this paper, we report an efficient segmentation and grain boundary detection process using modern image processing operators like simple linear iterative clustering and skeletonization. Accurate phase segmentation is the major requirement for any phase identification and quantification operations. The proposed image processing methods have been experimented on the in-house generated 48 scanning electron microscopy (SEM) microstructures obtained from plain carbon steel samples containing 0.1, 0.22, 0.35 and 0.48 wt%C and have been subjected to both annealing and normalizing treatments. The microstructures for dataset have been captured in SEM using secondary electron mode over a wide range of magnification × 500–× 5000. The experimental results significantly validate the segmentation of ferrite and pearlite regions. Also, the grain boundary detection results appear to be plausibly effective in case of ferrite–ferrite and ferrite–pearlite boundaries. However, the grain boundary detection efficiency is found to be relatively poor in case of pearlite–pearlite boundary. The overall performance of the proposed image processing technique in context of ferrite–pearlite steel SEM images shows promising results in all circumstances of compositional range, heat treatment and magnification. © 2019, The Institution of Engineers (India).

关键词： Microstructure

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Retraction Note: Enhancing destination image through virtual reality technology: the role of tourists’ immersive experience

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Current Psychology 2024年第2期44卷 1430-1430页

作者： Ghorbanzadeh, Davood AlHamad, Ahmad Qasim Mohammad Deng, Kuicthok Yak Alkurdi, Ahmed Alaa Hani Prasad, K. D. V. Sharbatiyan, Mohsen Department of Management and Social Science Islamic Azad University of Tehran North Branch Tehran Iran Department of Business Administration University of Sharjah Sharjah UAE Department of Business Management Lincoln University College Petaling Jaya Malaysia Department of Information Technology Duhok Technical College Duhok Polytechnic University Duhok Iraq Department of Computer Science College of Science Nawroz University Duhok Iraq Symbiosis Institute of Business Management Hyderabad India Department of Executive Master of Business Administration Faculty of Management Islamic Azad University of Tehran Central Branch Tehran Iran

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Efficient authenticated key establishment protocol for telecare medicine information systems

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AIP Conference Proceedings 2022年第1期2519卷

作者： Mahalakshmi R. Lokesh Kumar K. S. Ranjini S. Sindhu R. Udhayakumar 1Department of Mathematics School of Applied Sciences REVA University Bangalore Karnataka India 2Department of Analytics School of Computer Science and EngineeringVellore Institute of Technology Vellore -632014 Tamilnadu India 3Department of Computer Applications Dayanand Sagar college of Arts Science and Commerce Bangalore Karnataka India 4Department of Master of Computer Applications Cambridge Institute of Technology(VTU) Bengaluru India 5Department of Mathematics School of Advanced Sciences Vellore Institute of Technology Vellore -632014 Tamilnadu India

Secure checked based three person affirmation plot for records trade telecare remedy facts structures permits two customers simply store their verifiers prepared from their certifiable thriller state in approval verifiers informational index. By then the confirmation professional can test the clients’ verifiers and help them to exchange electronic medical records or electronic prosperity statistics securely and favorably. In this work, we must suggested protocol based on SPSD.

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Efficiënt load balancing by optimized flexi max-min algorithm

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Journal of Physics: Conference Series 2021年第1期1716卷

作者： P Praveen Kumar V Kanchana Devi Student Master of Computer Applications Vellore Institute of Technology Chennai Campus Tamilnadu India Associate Professor School of Computing Science and Engineering Vellore Institute of Technology Chennai Campus Tamilnadu India

Load Balancing is required to distribute tasks across Virtual Machines on one hand and on the other hand in a cloud Environment. Here, a new task scheduling algorithm: 'Optimized Flexi Max-Min Scheduling Algorithm' is proposed. The algorithm maintains a data structure which is modeled after a Binary Search Tree (BST) for estimations, enhanced searching, task allocation, and migration of tasks. Cloud-Sim is used to model and simulate the cloud computing environment in order to obtain simulated data. The result of this experiment shows that the proposed algorithm outperforms the traditional Max-Min task scheduling algorithms.

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Testing Big Data Application

Testing Big Data Application

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International Conference on Electrical Engineering, computer science and Informatics (EECSI)

作者： Narinder Singh Punn Sonali Agarwal M. Syafrullah Krisna Adiyarta Indian Institute of Information Technology Allahabad Prayagraj India Program of Master of Computer Science Universitas Budi Luhur Indonesia

Today big data has become the basis of discussion for the organizations. The big task associated with big data stream is coping with its various challenges and performing the appropriate testing for the optimal analysis of the data which may benefit the processing of various activities, especially from a business perspective. Big data term follows the massive volume of data, (might be in units of petabytes or exabytes) exceeding the processing and analytical capacity of the conventional systems and thereby raising the need for analyzing and testing the big data before applications can be put into use. Testing such huge data coming from the various number of sources like the internet, smartphones, audios, videos, media, etc. is a challenge itself. The most favourable solution to test big data follows the automated/programmed approach. This paper outlines the big data characteristics, and various challenges associated with it followed by the approach, strategy, and proposed framework for testing big data applications.

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A Third Order based Additional Regularization in Intrinsic Space of the Manifold

A Third Order based Additional Regularization in Intrinsic S...

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International Conference on Electrical Engineering, computer science and Informatics (EECSI)

作者： Rakesh Kumar Yadav Abhishek Shekhar Verma S Venkatesan M. Syafrullah Krisna Adiyarta Indian Institute of Information Technology-Allahbad Prayagraj India Program of Master of Computer Science Universitas Budi Luhur Indonesia

Second order graph Laplacian regularization has the limitation that the solution remains biased towards a constant which restricts its extrapolation capability. The lack of extrapolation results in poor generalization. An additional penalty factor is needed on the function to avoid its over-fitting on seen unlabeled training instances. The third order derivative based technique identifies the sharp variations in the function and accurately penalizes them to avoid overfitting. The resultant function leads to a more accurate and generic model that exploits the twist and curvature variations on the manifold. Extensive experiments on synthetic and real-world data set clearly shows that the additional regularization increases accuracy and generic nature of model.

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