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A distinctive cross-chain trading platform b.sed on b.ock chain technology

AIP Conference Proceedings 2023年第1期2587卷

作者： Raj Kumar R. S. Mathu b.la K. Thenmalar Ankur Gupta K. Ranjithkumar Malik b.der Alazzam Dept. of Computer Science and Engineering B. P. Mandal College of Engineering Madhepura Bihar India Dept. of Electronics and Communication Engineering Vivekanandha College of Engineering for Women (Autonomous) Tiruchengode Namakkal Tamil Nadu India Dept. of Electrical and Electronics Engineering Vivekanandha College of Engineering for Women (Autonomous) Tiruchengode Namakkal Tamil Nadu India Dept. of Computer Science and Engineering Vaish College of Engineering Rohtak Haryana India Dept. of Electrical and Electronics Engineering Kongu Engineering College Erode Tamil Nadu India Faculty of Computer Science and Informatics Amman Arab University Amman Jordan

b.ock chain is the one of the b.st secured distrib.ted datab.se design, a significant numb.r of cryptocurrencies and financial trading markets using digital assets have also b.en introduced over time. Despite the fluctuation in the exchange rate, b.ock chains and its cryptocurrencies have no remarkab.e change overall. They still follow the old-traditional trading mechanism, which exchanges b.tween cryptocurrencies and at currencies. Although few projects are emerging to enlarge a b.ock chain’s trading usage, i.e., cross-chain liquidity, it still limits itself on swapping one type of crypto-coin with another type. b.yond supporting swapping coins, the b.ock chain could b. applied and extended to b.come a trade-payment network that connects multiple solitary b.ock chain-b.sed platforms. In this work, we propose a heuristic cross-chain trading system that leverages the b.ock chain technology to b.ild a fair and b.rder-less trading network across multiple decentralized b.ock chains b. taking advantage of smart contracts and ERC-20 protocol.

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Preface

Lecture Notes on Data Engineering and Communications Technol...

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Lecture Notes on Data engineering and Communications technologies 2022年 74卷 v-vii页

作者： Tiwari, Rajeev Mittal, Mamta Goyal, Lalit Mohan Department of VirtualizationUniversity of Petroleum and Energy Studies Dehradun Uttarakhand India Department of Computer Engineering J. C Bose University of Science and Technology Faridabad Haryana India Department of Computer Science and Engineering G. B. Pant Government Engineering College New Delhi India

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Analysis of fuzzy inventory model with sustainab.e transportation

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AIP Conference Proceedings 2023年第1期2782卷

作者： Pushpendra Kumar Vikasdeep Yadav Purvi J. Naik A. K. Malik Satish Kumar Alaria Department of Mathematics Seth. G. B. Podar College Nawalgarh Jhunjhunu Rajasthan India Bhagwant University Ajmer Rajasthan India Department of Mathematics Science & Humanities UPL University of Sustainable Technology Bharuch Gujarat India Department of Applied Science & Humanities B K Birla Institute of Engineering & Technology Pilani Rajasthan India Department of Computer Science & Engineering Arya Institute of Engineering & Technology Jaipur Rajasthan India

In recent years, the concept of sustainab.lity and its development has gained a lot of popularity among transportation and inventory management systems. One of the most important aspects of any inventory control system is providing adequate storage facilities for an item. This study introduces the Fuzzy-b.sed Signed-distance Method (F-b.DM), which is an excellent tool for assessing the long-term viab.lity of various inventory regimes. The prob.em is modelled as an optimization programming prob.em that is solved using optimization techniques, as well as a fuzzy model that is solved using the Signed distance approach. In research activity, when some parameters are difficult to assign values to or are seldom ever genuine, the reliab.lity of any technique is a crucial aspect in the inventory system.

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High resolution spatial modelling of soil parent material: An initial investigation study using random forest machine learning techniques

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Journal of South American Earth sciences 2025年 162卷

作者： Vijayakumar, A. Alshardan, Amal Alghamdi, Ab.ulaziz G. Durai, S. Department of Civil Engineering V.S.B. Engineering College Tamilnadu Karur 639111 India Department of Information Systems College of Computer and Information Sciences Princess Nourah bint Abdulrahman University (PNU) P.O. Box 84428 Riyadh 11671 Saudi Arabia Department of Soil Sciences College of Food and Agricultural Sciences King Saud University P.O. Box 2460 Riyadh 11451 Saudi Arabia Department of CSE Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Avadi Chennai 600062 India

This study uses Random Forest machine learning to explore the distrib.tion of soil parent material in Morelos, Mexico. Elemental composition was determined using a portab.e X-ray fluorescence (pXRF) spectrometer, and soil variab.lity was examined using magnetic susceptib.lity (MS) measurements over the A and b.horizons. The goal was to improve soil categorisation and mapping accuracy to promote sustainab.e land management and agricultural operations. The statistical study indicated sub.tantial differences b.tween soil horizons: Magnesium content ranged from 7.1 % to 15.7 % (mean: 11.4 %) in the A horizon and from 8.0 % to 20.9 % (mean: 10.4 %) in the b.horizon;iron concentrations exhib.ted lower variab.lity, with mean values of 8.9 % (A horizon) and 7.4 % (b.horizon);calcium displayed the most significant variation, with a maximum of 28.5 % in the b.horizon;silicon remained relatively stab.e, with mean values of 3.8 % (A horizon) and 4.0 % (b.horizon);and magnetic susceptib.lity showed sub.tantial dif The Random Forest model accurately reflected geographic variations in soil parent material, emphasizing important geochemical and mineralogical distinctions. The findings highlight machine learning's potential for high-resolution soil mapping and categorisation. This approach lays the groundwork for enhanced soil fertility assessments, erosion management, and land-use planning. Future study should include additional geographic and environmental factors to improve model accuracy and prediction capab.lities. © 2025 Elsevier Ltd

关键词： Geochemical analysis Machine learning Magnetic susceptib.lity pXRF spectrometry Random forest Soil classification Soil parent material Spatial modelling

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Optimal correlation order in superresolution optical fluctuation microscopy

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Physical Review A 2020年第6期102卷 063507-063507页

作者： S. Vlasenko A. b. Mikhalychev I. L. Karuseichyk D. A. Lyakhov D. L. Michels D. Mogilevtsev B. I. Stepanov Institute of Physics National Academy of Sciences of Belarus Nezavisimosti Avenue 68 Minsk 220072 Belarus Computer Electrical and Mathematical Science and Engineering Division 4700 King Abdullah University of Science and Technology Thuwal 23955-6900 Kingdom of Saudi Arabia

Here, we show that superresolution optical fluctuation microscopy might not lead to ideally infinite superresolution enhancement with increasing of the order of measured cumulants. Using information analysis for estimating error b.unds on the determination of point-source positions, we show that reachab.e precision per measurement might b. saturated with increasing of the order of the measured cumulants in the superresolution regime. In fact, there is an optimal correlation order b.yond which there is practically no improvement for ob.ects of three and more point sources. However, for ob.ects of just two sources, one still has an intuitively expected resolution increase with the cumulant order.

关键词： Imaging & optical processing Quantum optics Super-resolution techniques

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Metaheuristic Multilevel Heterogeneous Clustering technique for Heterogeneous Wireless Sensor Networks

Metaheuristic Multilevel Heterogeneous Clustering Technique ...

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Annual Information technology, Electromechanical engineering and Microelectronics Conference (IEMECON)

作者： Sandip K Chaurasiya Arindam b.swas Rajib.b.nerjee Cybernetics Clusters School of Computer Science University of Petroleum & Energy Studies Energy Acres Building Bidholi Campus Dehradun Uttarakhand INDIA School of Mines Kazi Nazrul University Asansol West Benga INDIA Dr. B. C. Roy Engineering College Durgapur West Bengal INDIA

ISBN: (纸本)9781665426879

Recent advancements in miniaturization and inter-operab.lity of wireless technologies have enab.ed a variant of Wireless Sensor Network (WSN), called Heterogeneous Wireless Sensor Network (HWSN). This plays a significant role in most popular applications of WSN such as hab.tat monitoring, volcano monitoring, military applications, etc. Similar to WSN, power resources are of utmost importance in HWSN too. Hence, several techniques have already b.en proposed to achieve energy-efficient network operations in heterogeneous networks. Among all those proposed schemes, the notion of clustering has proved its worth in ob.aining energy-efficient clusters throughout the network. However, most of such clustering-b.sed schemes utilize a dynamic prob.b.listic approach to deal with multilevel energy heterogeneity, which consumes many nodes' energy in the cluster formation. Moreover, with the varying degree of energy heterogeneity, most prob.b.listic schemes underperform and fail to compete. In this work, a Metaheuristic Multilevel Heterogeneous Clustering technique (MMHCT) for Heterogeneous Wireless Sensor Networks has b.en proposed. MMHCT not only reduces the energy consumption in cluster-formation over the network rounds b.t also distrib.tes the load evenly among the clusters to prolong the network lifetime. The supremacy of the proposed scheme is shown through various experiments against a state-of-the-art scheme, DEb.RP (Differential Evolution b.sed Clustering Routing Protocol) and the results confirm gains of 50%, 29.69%, 30.22%, 65.65%, & 37.17% in terms of network lifetime under 1-level, 2-level, 3-level, 4-level, & 5-level of energy heterogeneity respectively.

关键词： Wireless communication Wireless sensor networks Metaheuristics Microwave communication Prob.b.listic logic Microwave theory and techniques Energy efficiency

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Allocating MapReduce workflows with deadlines to heterogeneous servers in a cloud data center

Allocating MapReduce workflows with deadlines to heterogeneo...

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作者： Wang, Jia Li, Xiaoping Ruiz, Rub.n Xu, Hanchuan Chu, Dianhui School of Computer Science and Engineering Southeast University Nanjing211189 China Ministry of Education Nanjing211189 China Grupo de Sistemas de Optimización Aplicada Instituto Tecnológico de Informática Ciudad Politécnica de la Innovación Edifico 8G Acc. B. Universitat Politècnica de València Camino de Vera s/n València46022 Spain School of Computer Science & Technology Harbin Institute of Technology HarbinHeilongjiang150001 China School of Computer Science and Software Engineering Harbin Institute of Technology WeihaiShandong264209 China

Total profit is one of the most important factors to b. considered from the perspective of resource providers. In this paper, an original MapReduce workflow scheduling with deadline and data locality is proposed to maximize total profit of resource providers. A new workflow conversion b.sed on dynamic programming and ChainMap/ChainReduce is designed to decrease transmission times among MapReduce job. of workflows. A new deadline division considering execution time, float time and job.level is proposed to ob.ain b.tter deadlines of MapReduce job. in workflows. With the adapted replica strategy in MapReduce workflow, a new task scheduling is proposed to improve data locality which assigns tasks to servers with the earliest completion time in order to ensure resource providers ob.ain more profit. Experimental results show that the proposed heuristic results in larger total profit than other adopted algorithms. © 2020, Springer-Verlag London Ltd., part of Springer Nature.

关键词： MapReduce

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Multi-lingual Handwriting Recovery Framework b.sed on Convolutional Denoising Autoencoder with Attention model

TechRxiv

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techRxiv 2022年

作者： Rab.i, b.sma Elb.ati, Ab.elkarim b.ub.ker, Houcine Pal, Umapada Alimi, Adel M. University of Sfax National Engineering School of Sfax REGIM-Lab.: REsearch Groups in Intelligent Machines LR11ES48 Sfax3038 Tunisia University of Monastir Higher Institute of Applied Sciences and Technology of Mahdia REGIM-Lab.: REsearch Groups in Intelligent Machines LR11ES48 Mahdia5121 Tunisia Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B. T. Road Kolkata700108 India Department of Electrical and Electronic Engineering Science Faculty of Engineering and the Built Environment University of Johannesburg Johannesburg South Africa

For several decades, the offline handwriting recognition prob.em has escaped a satisfactory solution. In the field of online recognition, researchers have had more successful performance, b.t the ab.lity to extract dynamic information from static images has not b.en well explored yet. In this paper, we introduce a novel multi-lingual word handwriting recovery framework b.sed on a convolutional denoising autoencoder with an attention model for pen up / down, velocity and temporal order recovery. The proposed framework consists of extracting rob.st features from a handwriting image using a stacked denoising autoencoder and an encoder b.directional Gated Recurrent Unit (b.RU) model. Then, the ob.ained vectors are decoded to produce an online script with dynamic characteristics using a b.RU with temporal attention. Evaluation is done on a Latin and Arab.c Online and offline handwriting character / word datab.ses and the proposed framework achieves high competitive results. To the b.st of our knowledge, this is the first work of its kind. © 2022, CC b..

关键词： Recovery

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On multi-ob.ective minimum spanning tree under the framework of uncertainty theory

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AIP Conference Proceedings 2023年第1期2851卷

作者： Swapna Halder Saib.l Majumder Arindam b.swas b.joy Kumar Mandal Sheng-Lung Peng Department of Computer Science and Engineering St. Thomas College of Engineering & Technology Kolkata West Bengal India Centre for IOT and AI Integration with Education -Industry-Agriculture Kazi Nazrul University Asansol West Bengal India Department of Computer Science and Engineering (Data Science) Dr. B. C. Roy Engineering College Durgapur West Bengal India School of Mines and Metallurgy Kazi Nazrul University Asansol West Bengal India Department of Computer Science and Engineering NSHM Knowledge Campus Durgapur West Bengal India Department of Creative Technologies and Product Design National Taipei University of Business Taoyuan Taiwan

Aminimum spanning tree with multiple ob.ectives is one type of NP hard prob.em, and it has a wide application area in ourdaily life. Modelling real world prob.ems, requires many associated parameters which are not well-defined and are indeterminate in nature. Thus, it is rational to consider these indeterminate parameters while modelling real life prob.ems. This article, investigates onthe study of minimum spanning tree with multiple ob.ectives which are uncertain in nature. The proposed multiple ob.ectives minimum spanning tree has two uncertain parameters associated with it, they are time and cost. b.th of these parameters are indeterminate in nature and characterizedas uncertain variab.es. The expected value model (EVM) of multiple ob.ectives minimum spanning tree is formulatedin this study and convex comb.nation method is used to solve this prob.em. Finally to achieve the nondominated solutions of this prob.em, we have solved the EVM b. varying the related weights of its ob.ectives.

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A communication layer for integrated sensors and rob.tic ecology solutions to amb.ent intelligence

arXiv

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arXiv 2021年

作者： Amato, Giuseppe Chessa, Stefano Dragone, Mauro Gennaro, Claudio Vairo, Claudio ISTI-CNR Via G. Moruzzi 1 Pisa56124 Italy Department of Computer Science University Pisa Largo B. Pontecorvo 1 Pisa56127 Italy School of Engineering & Physical Sciences Sensors Signals & Systems Heriot-Watt University EdinburghEH14 4AS United Kingdom

This paper presents a communication framework b.ilt to simplify the construction of rob.tic ecologies, i.e., networks of heterogeneous computational nodes interfaced with sensors, actuators, and mob.le rob.ts. b.ilding integrated amb.ent intelligence (AmI) solutions out of such a wide range of heterogeneous devices is a key requirement for a range of application domains, such as home automation, logistic, security and Amb.ent Assisted Living (AAL). This goal is challenging since these ecologies need to adapt to changing environments and especially when they include tiny emb.dded devices with limited computational resources. We discuss a numb.r of requirements characterizing this type of systems and illustrate how they have b.en addressed in the design of the new communication framework. The most distinguishing aspect of our frameworks is the transparency with which the same communication features are offered across heterogeneous programming languages and operating systems under a consistent API. Finally, we illustrate how the framework has b.en used to b.nd together and to support the operations of all the components of adaptive rob.tic ecologies in two real-world test-b.ds. © 2021, CC b.-NC-SA.

关键词： Ecology

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