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7th international conference on Cognitive Systems and Information Processing, ICCSIP 2022

7th International Conference on Cognitive Systems and Inform...

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7th international conference on Cognitive Systems and Information Processing, ICCSIP 2022

ISBN: (纸本)9789819906161

The proceedings contain 47 papers. The special focus in this conference is on Cognitive Systems and Information Processing. The topics include: Mastering "Gongzhu" with Self-play Deep Reinforcement Learning;improved Vanishing Gradient Problem for Deep Multi-layer Neural networks;incremental Quaternion Random Neural networks;question Answering on Agricultural Knowledge Graph Based on Multi-label Text Classification;dairy Cow Individual Identification System Based on Deep Learning;automatic Packaging System Based on Machine Vision;meteorological and Hydrological Monitoring technology Based on Wireless Sensor network Model and Its Application;a Review of Deep Reinforcement Learning Exploration Methods: Prospects and Challenges for Application to Robot Attitude Control Tasks;aeroBotSim: A High-Photo-Fidelity Simulator for Heterogeneous Aerial Systems Under Physical Interaction;T3SFNet: A Tuned Topological Temporal-Spatial Fusion network for Motor Imagery with Rehabilitation Exoskeleton;trailer Tag Hitch: An Automatic Reverse Hanging System Using Fiducial Markers;anatomical and Vision-Guided Path Generation Method for Nasopharyngeal Swabs Sampling;a Hierarchical Model for Dynamic Simulation of the Fault in Satellite Operations;design and Implementation of Autonomous Navigation System Based on Tracked Mobile Robot;towards Flying Carpet: Dynamics Modeling, and Differential-Flatness-Based Control and Planning;region Clustering for Mobile Robot Autonomous Exploration in Unknown Environment;human Intention Understanding and Trajectory Planning Based on Multi-modal Data;Robotic Arm Movement Primitives Assembly Planning Method Based on BT and DMP;center-of-Mass-Based Regrasping of Unknown Objects Using Reinforcement Learning and Tactile Sensing;alongshore Circumnavigating Control of a Manta Robot Based on Fuzzy Control and an Obstacle Avoidance Strategy;joint Trajectory Generation of Obstacle Avoidance in Tight Space for Robot Manipulator;robot Calligraphy Based on Footprint Mo

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A Fair and Reliable Data Trading Scheme based on Blockchain 2

A Fair and Reliable Data Trading Scheme based on Blockchain

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2nd international conference on computer Science and Blockchain, CCSB 2022

作者： Wu, Zhili Pan, Heng Si, Xueming Qian, Haiyang Cai, Fugang Henan International Joint Laboratory of Blockchain and Data Sharing Zhengzhou Henan China Henan Key Laboratory of Network Cryptography Technology Zhengzhou Henan China Zhongyuan University of Technology The Frontier Information Technology Research Institute China Shanghai Jiao Tong University Department of Computer Science and Engineer Shanghai China

ISBN: (纸本)9798350331882

To solve the single point of failure and opaque transaction problems in the current centralized data trading model, we propose a blockchain-based data trading scheme. Firstly, we construct a blockchain-based data transaction model to provide users with peer-to-peer trusted transaction services. Then, we design a two-stage one-to-many data pricing method based on smart contracts and the Rubinstein model, which can guarantee the reasonableness of data transaction pricing and achieve a fair price between a single data demander and multiple data owners. Next, we suggest a forensic dispute arbitration method based on on-chain and off-chain data collaboration and a data integrity verification method, which aims to ensure the reliability of de-centralized data transactions and prevent malicious acts such as data owners providing false data, data requesters refusing to pay, and data stored in the cloud being tampered with. Finally, we perform experiments based on consortium blockchain. Experimental results show that the scheme of this paper has better functionality and performance than other schemes of data transactions. © 2022 IEEE.

关键词： Smart contract

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Feature Pyramid Boosting network for Rendering Natural Bokeh

Feature Pyramid Boosting Network for Rendering Natural Bokeh

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2022 IEEE international conference on Multimedia and Expo, ICME 2022

作者： Liu, Yi Zhang, Juncheng Liao, Qingmin Ma, Haoyu Liu, Shaojun Shenzhen International Graduate School Tsinghua University Shenzhen518055 China College of Health Science and Environmental Engineering Shenzhen Technology University China

ISBN: (数字)9781665485630

ISBN: (纸本)9781665485630

Natural bokeh is a typical characteristic of digital single-lens reflex (DSLR) cameras and high-quality lenses, which is commonly used to emphasize a subject from a distracting background. However, it is still a big challenge for mobile platforms to produce similar effects due to the small apertures of their lenses. Unlike many previous methods formulated as a two-stage task composed of depth/defocus estimation and defocus magnification, we propose a feature pyramid boosting network with novel hierarchical attention modules to render bokeh in one step. In addition, existing learning-based methods suffer from the pixel misalignment of the datasets. We present a well-aligned bokeh dataset captured by a DSLR to address this problem. Experiments show that our method can render comparable bokeh with the state-of-the-art method but requires fewer parameters. © 2022 IEEE.

关键词： computer vision

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An Investigation on the Impact of Energy Harvesting in Green IoT with Netsims 1

An Investigation on the Impact of Energy Harvesting in Green...

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1st international conference on Information System and Information technology, ICISIT 2022

作者： Ahmad, Mohd Nabil Iqbal Bin Sajak, Aznida Binti Abu Bakar Ismail, Mohd Nazri Bin Allias, Noormadinah Universiti Kuala Lumpur Miit Computer Engineering Technology Kuala Lumpur Malaysia Universiti Pertahanan Nasional Malaysia Department of Computer Science Kuala Lumpur Malaysia Albukhary International University School of Computing and Informatics Alor Setar Kedah05200 Malaysia

ISBN: (数字)9781665402002

ISBN: (纸本)9781665402002

Real-world applications such as habitat monitoring, air quality, natural disaster prevention, smart agriculture, and smart building are possible due to the utilization of Wireless Sensor networks (WSNs). However, in most cases, classic WSN nodes are fueled by non-rechargeable batteries with a limited capacity for energy storage. In this paper, a solar energy harvesting implementation is proposed in a wireless sensor network to increase the lifetime of each sensor node. The implementation may also ideally achieve an infinite lifetime. Nevertheless, there are many other obstacles to overcome and consider in solar energy harvestings, such as temperature fluctuations, solar panel conversion efficiency, solar energy forecasting difficulties, power interruptions, and other environmental or natural phenomenon issues. Therefore, the objective of this research is to review the recent literature on energy harvesting for wireless sensor networks focusing on solar ambient light energy. Using NETSIM simulations, the goal of this investigation would be to achieve reliability and energy efficiency in wireless sensor networks through solar energy harvesting. © 2022 IEEE.

关键词： Energy harvesting

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Machine Automatic Translation Evaluation Based on Big Data algorithms 2

Machine Automatic Translation Evaluation Based on Big Data A...

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2nd international conference on Data Science and Information System, ICDSIS 2024

作者： Xia, Bing Heilongjiang International University Harbin China

ISBN: (纸本)9798350381665

Currently,research on machine translation is mainly divided into four stages: dictionary matching method, comprehensive linguistic knowledge method, corpus based statistical machine translation, and neural machine translation. Machine translation evaluation is a hot topic in current machine translation research, which can effectively identify defects in translations and improve translation quality. The evaluation of translation quality can be divided into two types: manual evaluation and computer evaluation. Manual evaluation has higher accuracy due to being completed in the early stages, but manual evaluation requires a lot of manpower. In addition, human evaluation has a certain degree of subjectivity. The rise of automated evaluation technology has made up for the shortcomings of traditional manual evaluation methods. The BP (back propagation) algorithm discussed in this article can quickly evaluate translations and has higher efficiency compared to manual evaluation. At present, most machine translation evaluation methods evaluate the quality of a translation based on the similarity between the translation and the reference translation. Therefore, in the evaluation process, the amount of translation materials cited by the translator and the utilization rate of the obtained materials are the key factors determining the effectiveness of the evaluation method. This article used the BP algorithm to overcome the bottleneck problem of overly relying on sample data, extract feature vectors of translations well, and improve the accuracy of translation evaluation. Finally, this article verified through experiments that the machine translation automatic evaluation model based on deep learning algorithms was lower than other models, and its error rate remained below 0.24. © 2024 IEEE.

关键词： Big data

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Banking Data Enrichment Pipeline 22

Banking Data Enrichment Pipeline

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8th international conference on computer technology Applications, ICCTA 2022

作者： Doshi, Ronak Srinivasaraghavan, Gg Bansal, Neeraj Gupta, Amit Department of Electronics and Communication International Institute of Information Technology Bangalore India Department of Computer Science International Institute of Information Technology Bangalore India Canopy Pvt Ltd. Singapore Singapore

ISBN: (纸本)9781450396226

In the present day, there has been a rapid growth of fintech companies all around the globe, providing services like market data analytics, banking solutions, mobile banking, expense management, etc. Many such fin-tech companies rely majorly on banking data. However, bank data, like transactions and holdings data, contains very concise intricate string descriptions which are not machine readable. These string descriptions do not follow any standardized protocols making them harder to convert it into organized data. Hence we propose an intelligent data enrichment pipeline that employs deep-learning based BERT model to classify the transaction contract type and advanced algorithms like suffix tree and tools like regular expression to extract all the valuable information. The pipeline returns categorized and structured machine readable data objects which can form the backbone of all the fintech software. We were able to achieve contract type classification accuracy of 98.4% and were able to extract all the valuable data from the string description. In order to understand the working of the BERT based deep-learning model, we reverse engineered the model using attention networks. The results of the same are also presented in this paper. © 2022 ACM.

关键词： Pipelines

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A GI Tract Image Segmentation Algorithm Via UNet 2.5D network 3

A GI Tract Image Segmentation Algorithm Via UNet 2.5D Networ...

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3rd international conference on Big Data, Artificial Intelligence and Internet of Things Engineering, ICBAIE 2022

作者： Zhang, Xuyang Yue, Xiao Liu, Tianjing Wu, Siwen Anhui University Hefei China University of Science and Technology of China Hefei China United International College Beijing Normal University Hong Kong Baptist University Zhuhai China Renmin University of China Shanghai China

ISBN: (数字)9781665451604

ISBN: (纸本)9781665451604

Digestive tract tumor is the most common malignant tumor, which seriously threatens human health. Therefore, there is an urgent need for the improvement of tumor treatment technology. With the development of computer science and technology and the innovation of hardware equipment, the research on computer aided diagnosis (CAD) [9] has been widely carried out. In our paper, we utilize U-Net2.5D for stomach and intestines' segmentation, which could assist radiation oncologists to deliver high doses of radiation using X-ray beams pointed to tumors while avoiding the stomach and intestines. We choose dice similarity efficiency (DSC) as our experiment metrics. The higher DSC is, the more accuracy the segmentation will gain. The results show that our Unet2.5D(EfficientNetB1) owns the best performance with 0.841 DSC, which is 0.087, 0.093, 0.029 higher than Unet(ResNet50), Unet(EfficientNetB0) and Unet(EfficientNetB1) respectively. © 2022 IEEE.

关键词： Efficiency

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A Novel Artificial Intelligence Inspired Approach for Analysing Sentiments using Neural network 1

A Novel Artificial Intelligence Inspired Approach for Analys...

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1st international conference on Smart and Sustainable Technologies in Energy and Power Sectors, SSTEPS 2022

作者： Thakral, Deepti Sharma, Sachin Sharma, Khushi Ranjan, Sudhakar Apeejay Stya University School of Engineering and Technology Gurugram India Manav Rachna International Institute of Research and Studies Faculty of Computer Applications Faridabad India Amity University Department of Computer Engineering Noida India

ISBN: (纸本)9781665464147

Sentiment Analysis is a text classification system used to analyse the incoming text and determine if the sentiment evolved from the argument text is positive, negative or neutral. It holds specific significance in different areas of technology and it has varied applications. It combines the power of two most significant fields of Artificial Intelligence, viz. Deep Learning and Natural Language Processing. Deep Learning has evolved as an advanced and efficient technology to target and solve real-world problems with greater accuracy and efficiency. Neural networks are used to deal with enormous amounts of data without any considerable domain engineering and adapt from its own method of computing. Sentiments within a text can become misleading if the whole sentence is taken as a collection of independent words, since each and every word is connected to other in some sense. This research is used to propose and develop an efficient model that can analyse the sequential sentiments with greater prediction and accuracy. This research also compares the prediction accuracy of the proposed model with other existing novel methods. © 2022 IEEE.

关键词： Sentiment analysis

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Disease Diagnosis in Grapevines – A Hybrid Resnet-Jaya Approach 1

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11th international Advanced Computing conference, IACC 2021

作者： Mishra, Piyush Mohapatra, Puspanjali Patra, Tapas Kumar Subham, P. Turing Centre for Living Systems Aix-Marseille University Marseille France Department of Computer Science Engineering International Institute of Information Technology Bhubaneswar India Department of Instrumentation and Electronics Engineering Odisha University of Technology and Research Bhubaneswar India Department of Computer Science Engineering National Institute of Technology Rourkela India

ISBN: (数字)9783030955021

ISBN: (纸本)9783030955014

Different diseases in grapevines have different kinds of effects on the various parts of the plant, the most drastic of such abnormalities easily seen in the leaves of the grapevines. Detection, diagnosis and prevention of diseases that could hinder the production and utilisation of the grapevine are of prime importance in viticulture. In view of the multiple hazards associated with viticulture, it is worthwhile to build on the optimisation and automation in the field. This study presents a methodology to marry the different aspects of computational mechanisms, i.e. neural network approaches along with different optimisation approaches, and apply them to diagnose the diseases that a said grapevine might suffer from. The objectives were, thus: (1) to be able to identify which disease corresponds to the effects shown in the leaves of the particular grapevine, (2) to make a robust identification mechanism by using methodologies of deep learning and soft computing, and (3) to make use of different such methodologies and infer which of those methodologies would work the best in this context. As a result, we mostly compared a 10 layer-feed forward neural network with a 34 layer-Resnet. We also employed other CNN methodologies like Densenet, VGG and Alexnet but found that they did not provide the best results in this context. Further, we hybridised these approaches with several optimisation algorithms, like the Jaya Algorithm, the Genetic Algorithm, the Particle Swarm Optimisation Algorithm, etc. We found that a hybrid Resnet-Jaya model gave the best output without overfitting, at 99.71%. © 2022, Springer Nature Switzerland AG.

关键词： Diagnosis

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Mining of Online Communication network of National Traditional Sports Culture based on computer New Media technology

Mining of Online Communication Network of National Tradition...

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2022 international conference on Edge Computing and Applications, ICECAA 2022

作者： Ke, Yi Physical Education School International School of Equestrian Wuhan Business University HuBei Wuhan430056 China

ISBN: (数字)9781665482325

ISBN: (纸本)9781665482325

The inheritance mechanism of national traditional sports culture is defined, and the connotation is explained, and five dimensions of driving mechanism, implementation mechanism, expression mechanism, guarantee mechanism and feedback mechanism are proposed to present the inheritance mechanism of national traditional sports culture in this paper. Moreover, the inheritance function of national traditional sports is optimized, new media and new technologies are innovated and integrated, the vigorous development of national traditional sports is comprehensively promoted, and the creative vitality of national culture is stimulated. This work further continues to inject vitality into inheritance, promote the development of national traditional sports industry, revitalize the consumption potential of the masses and the consumer market, take cultural protection and innovation as the concept, and broaden the way of inheritance. © 2022 IEEE.

关键词： Sports

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