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Study on nondestructive testing of milk varieties based on hyperspectral image technology 3

Study on nondestructive testing of milk varieties based on h...

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3rd IEEE international conference on Communications, Information System and computer Engineering, CISCE 2021

作者： Liu, Mei-Chen Xue, He-Ru Liu, Jiang-Ping College of Computer and Information Engineering Inner Mongolia Agricultural University Hohhot China

ISBN: (纸本)9780738112152

At present, there are few studies on the classification of milk varieties. In this experiment, we used hyperspectral spectrometer (400-1000nm) to study the classification of five milk with different fat content. The collected spectral data were preprocessed by normalization, standardization and multiple scattering correction (MSC), and the MSC method was selected according to the correction effect. The competitive adaptive heavy weights (CARS) were used to select the characteristic variables, and 20 characteristic bands with less redundant information were finally extracted. Data classification modeling was carried out, and the support vector machine algorithm (SVM) of RBF kernel function was selected, and the final classification accuracy of characteristic bands was 97.33%.The classification accuracy of K-Nearest Neighbor (KNN) algorithm reached 98.66%. The experimental results show that hyperspectral reflectance data can provide a new fast and nondestructive method for the classification and detection of dairy varieties. © 2021 IEEE.

关键词： Support vector machines

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Whole-building Energy Co-simulation for Dynamic Occupant-based Heating and Cooling Control with Rule-based and Q-learning algorithms 3

Whole-building Energy Co-simulation for Dynamic Occupant-bas...

引用

3rd IEEE international conference on Frontiers Technology of Information and computer, ICFTIC 2021

作者： An, Tongrui Ealing International School Liaoning Dalian China

ISBN: (纸本)9781665406055

Commercial building has become one of the most energy-consuming fields, which is as the similar level as transportations and industries. The majority of energy consumption in a commercial building is derived from heating ventilation and air conditioning (HVAC) system. Previously, the indoor temperature was mostly regulated by a fixed control strategy, without varying on the basis of other dynamic factors such as occupancy schedules, which leads to huge amount of energy waste. To optimize this control strategy for energy consumption reduction, this research study has employed two algorithm methods of rule-based control and tabular Q-learning control to achieve the dynamic control to reduce building energy consumption with agent-based stochastic occupancy simulator. As a result, with rule-based control, the simulation result has shown total energy consumption saves approximately 24% site energy annually compared to baseline control. In addition, the result derived from tabular Q-learning has shown 10% savings could be achieved during the cooling season with the optimal policy based on the defined action space and state space. In the future, both rule-base control and Q-learning control used for the cosimulation in this study are expected to be applied in more and more commercial buildings to achieve energy savings and economic benefits. © 2021 IEEE.

关键词： Energy utilization

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A Generalized Distance-Based Total Uncertainty Measure in Complex Evidence Theory 3

A Generalized Distance-Based Total Uncertainty Measure in Co...

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2021 3rd international conference on computer modeling, simulation and algorithm, cmsa 2021

作者： Huang, Xiumei Zhang, Yuanping Yang, Ming Hao, Yunzhi College of Computer and Information Science Southwest University Chongqing China College of Artificial Intelligence Southwest University Chongqing China

In this paper, a generalized total uncertainty (GTU) measure method is presented directly under the complex evidence theory framework, rather than under the probability framework. GTU is defined based on the distance between the belief interval of each singleton and the most uncertain case, which is normalized by the normalization factor. We proved the properties of GTU. There is an average evidence that represents the average acceptable environment for data from sensors. According to the GTU difference of each data and the average evidence, data from different sensors are given different weights. Each weight represents the trustworthiness of each sensor data in the fusion process, and giving a low weight to abnormal data can avoid false conclusions. The practicability and rationality of the method are verified by numerical examples and applications. © Published under licence by IOP Publishing Ltd.

关键词： Numerical methods

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algorithm of Handwritten String Segmentation Based on Recursive Rraining in Background Domain 3

Algorithm of Handwritten String Segmentation Based on Recurs...

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2021年第三届先进计算机技术、信息科学与通信国际会议(CTISC2021)

作者： LUO Jia HE Kai-lin DING Xiao-feng Computer Department Sichuan University Jinjiang College

ISBN: (纸本)9781665418683

How to accurately cut the handwritten string especially the sticky string, has become a key part of recognizing handwritten strings. Aiming at the traditional segmentation algorithm has some problems, such as more complex?the segmentation effect is not good and so on, this paper proposes a segmentation algorithm based on background domain recursive training. This algorithm is a common algorithm for handwritten digit string segmentation and English string segmentation. The principle is the use of handwritten string at the adhesion of the background domain features and recursive neural network RNN fusion of special mechanisms. It completes by modeling, training and implementation of three steps. RNN modeling is the core of the algorithm, it contain two important parts:(1)Assignment for the background domain, extracting the eigenvector value of the depression area by the principle of adjacent matching, the connection weights of the RNN input layer are calculated.(2) Using the minimum area selection principle to modify eigenvector values in the RNN's acceptance layer, the connection weight of the layer are calculated agin. After modeling completion, RNN is training samples?studying and remembering. Finally, use the knowledge that RNN has learned to complete real segmentation, the effect is satisfactory.

关键词： Training Information science Handwriting recognition Recurrent neural networks Adhesives Feature extraction Depression

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Design of Hybrid Wireless Network on Chip and Maximum Three Hops Routing algorithm 3

Design of Hybrid Wireless Network on Chip and Maximum Three ...

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3rd international conference on Applied Machine Learning, ICAML 2021

作者： Liu, Yuling School of Computer Science and Technology Engineering Tiangong University Tianjin300387 China

ISBN: (纸本)9781665421256

With the continuous expansion of network on chip scale, the traditional wired connection mode will cause a significant increase in the wiring complexity and network communication delay. The reasonable use of on-chip micro antenna makes wireless communication between nodes in the on-chip network possible. Wireless communication greatly improves the packet transmission efficiency and reduces the transmission delay and power consumption. Therefore, a novel hybrid wireless network on chip architecture is proposed. And through this architecture, we can realize a novel routing algorithm - the maximum three hops routing algorithm. The simulation results show that Compared with the classical routing algorithms such as XYZ (XY), West first and North last, the proposed method has remarkable effect in average routing hops, network delay and power consumption. © 2021 IEEE

关键词： Network-on-chip

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A Method to Handle Unstable Time Series in Anomaly Detection Problem 3

A Method to Handle Unstable Time Series in Anomaly Detection...

引用

3rd international conference on Control Systems, Mathematical modeling, Automation and Energy Efficiency, SUMMA 2021

作者： Gaev, Andrey Lantsberg, Anna Bauman Moscow State Technical University Department of Computer Systems and Networks Moscow Russia

ISBN: (纸本)9781665439817

Time series analysis is a well-known problem solved in many spheres of human activity. This analysis is most widely used in the tasks of tracking the state of any processes-checking stability of working machines in factories, tracking the rhythm of the heartbeat, and so on. One of the important tasks is decrease time to identify deviations in these processes, which reduces the cost of their elimination. A well known name for such tasks is anomaly detection and they belong to one-class classification problem. It is known that in order to effectively solve this type of problem, the spread of data within the training dataset should be taken into account. In this paper, we present a method that allows us to reduce intra-class data variation by automatically searching for and excluding unstable parts from the time series. The application of this method is considered as part of an algorithm that can be used to represent raw samples of time series as vectors suitable for further work with machine learning models. The algorithm has been tested on boundary-based machine learning methods such as One-class Support Vector Machine (OCSVM), Isolation Forest and Local Outlier Factor (LOF). Our dataset consists of time series from gas sensor, which are reflect sensor's sensitive surface reaction to several gases appearing in the environment. © 2021 IEEE.

关键词： Anomaly detection

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Underwater Sonar Image Segmentation by a Novel Joint Level Set Model 3

Underwater Sonar Image Segmentation by a Novel Joint Level S...

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3rd international conference on modeling, simulation, Optimization and algorithm, ICMSOA 2021

作者： Wang, Yue Zhou, Kefa Tian, Wei Chen, Zhe Yang, Dewei Computer and Information College Hohai University Nanjing211100 China Nanjing Hydraulic Research Institute Nanjing210029 China Country Dam Safety Management Center of the Ministry of Water Resources Nanjing210029 China

This paper proposes a novel joint level set model for underwater sonar image segmentation. Combining features in points and regions in our novel joint level set (LS), it can achieve excellent performance for underwater sonar image segmentation. Regional information guides the model to locate the object of interest, whereas the point information accurately delineates contours. In addition, the unified Markov random field (UMRF) is taken to measure the neighboring relation between points and regions, which can overcome the problems of the high speckle noise, strong bias and low resolution of underwater sonar images. Our novel model can segment underwater sonar images into three partitions, such as the objects of interest, shadow and backgrounds. In contrast to current segmentation methods, outstanding results are demonstrated by our model. Moreover, another advantage of our model lies in its high efficiency. © Published under licence by IOP Publishing Ltd.

关键词： Image segmentation

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Research on information communication dispatching method of smart grid based on VR technology 3

Research on information communication dispatching method of ...

引用

3rd IEEE international conference on Communications, Information System and computer Engineering, CISCE 2021

作者： Sun, Xiaolin Shen, Xueliang Zhu, He Yang, Xinke Fang, Zhonghua State Grid Xiong'an New Area Electric Power Supply Company Hebei China Pinggao Group Co. Ltd. Henan China

ISBN: (纸本)9780738112152

In order to improve the dispatching efficiency of smart grid information communication, reduce the load of smart grid, and ensure the security of power grid operation, a smart grid information communication scheduling method based on VR technology is proposed. The 3D modeling of substations and towers in smart grid power equipment is completed by 3DMAX software, and the 3D modeling of overhead lines, cables and other ancillary simple equipment is completed by skyline software;The virtual environment of smart grid integrating viewing and listening is constructed by combining virtual reality 3D technology, and dynamic dispatching priority is assigned by task value characteristic model and task time characteristic model. This process realizes the information communication dispatching of smart grid. The experimental results show that the method can effectively realize the whole station and equipment simulation of smart grid, and ensure the safe operation of smart grid;the scheduling rate of important tasks of smart grid information communication is always around 0.95, and the load deviation is less than 0.25, and it has the advantage of high dispatching efficiency. © 2021 IEEE.

关键词： 3D modeling

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Research on the motion law of rod pumps based on digital twin technology 3

Research on the motion law of rod pumps based on digital twi...

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3rd international conference on Intelligent Control, Measurement and Signal Processing and Intelligent Oil Field, ICMSP 2021

作者： Shen, Fei Ren, Shuang Shuang Zhang, Xiang Yang Luo, Hong Wu Feng, Min Chao Fu, Zhan Bao Northwest Branch of China Petroleum Exploration and Development Research Institute Gansu Province Lanzhou730000 China Key Laboratory of Internet of Things CNPC

ISBN: (纸本)9781665437158

In the process of rod pump lifting, the study on the movement law of rod pump and the distribution of liquid pressure and velocity in the valve barrel of the rod pump is an important basis for judging whether the oil well is normal or not and putting forward effective measures. This paper uses the simulation software platform, combined with the physical model of the laboratory, digital modeling. At the same time, a digital twinning method based on digital twinning model is proposed to analyze the movement law of rod pump. This method can solve the transparency of the production site, and can also make quantitative analysis, draw conclusions of construction significance, and guide the site effectively. © 2021 IEEE.

关键词： computer software

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Copy-Move Image Forgery Detection Using SURF, SIFT, and KAZE 3rd

Copy-Move Image Forgery Detection Using SURF, SIFT, and KAZE

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3rd international conference on Machine Learning, Advances in Computing, Renewable Energy and Communication, MARC 2021

作者： Rani, Anuj Jain, Ajit Department of Computer Science Banasthali Vidyapith Rajasthan Tonk India Department of Computer Science G L Bajaj Institute of Technology and Management Greater Noida India

ISBN: (纸本)9789811928277

In this digital world, image forgery is the most common cause for any digital forgery. Nowadays, people accept digital images blindly, even without checking their integrity and authenticity. One of the critical facts in digital image forensics is that we need to keep high confidence in forgery detection algorithms. In this work, multiple image forger detection algorithms are evaluated to check their efficacy using their detection accuracy and execution time. Discrete wavelet transform (DWT) is used for image decomposition at the preprocessing stage. The objective of this work is to suggest a best copy-move forgery detection algorithm among SIFT, SURF, and KAZE. For modeling the code, MATLAB is used as a programming language. Using the SURF algorithm, the accuracy rate is 56.50% with average execution time 1.28 s, while it is 66.75% and 2.78 s using SIFT. The detection rate by using the KAZE algorithm is reported as 61.24% with execution time is 1.50 s. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Discrete wavelet transforms

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