Abstract—With the intensification of the aging of China's population, the accompanying problems of aging and sub-replacement fertility have become increasingly prominent, and traditional senior care methods are challenging to meet the increasing demand for senior care service. As a new way of senior care derived from the background of big data, intelligent senior care has expanded a new space for the cause of senior care service in China in the new era and provided a new scientific and practical way to solve the senior care problems. This paper takes big data, the Internet of Things, cloud computing, and other information technologies as the core, designs and evaluates a cloud platform for intelligent senior care service, and builds a five-layer platform architecture of perception layer, application layer, interface layer, and business layer, the processing layer, and the big data layer. Six major systems realize the cloud platform display of intelligent senior care service: call and service system, data and information management system for the elderly, senior care meal assistance service system, sojourn senior care service system, elderly health management system, and volunteer service system. It effectively meets the needs of the elderly in terms of safety care, emergency assistance, healthy life, spiritual care, etc., and realizes the intelligence, informatization, dataization, and convenience of elderly care.
{"title":"Design and Implementation of Intelligent Senior Care Service Cloud Platform System in the Context of Big Data","authors":"Weiwei Kong, Sijia Du","doi":"10.1145/3569966.3570072","DOIUrl":"https://doi.org/10.1145/3569966.3570072","url":null,"abstract":"Abstract—With the intensification of the aging of China's population, the accompanying problems of aging and sub-replacement fertility have become increasingly prominent, and traditional senior care methods are challenging to meet the increasing demand for senior care service. As a new way of senior care derived from the background of big data, intelligent senior care has expanded a new space for the cause of senior care service in China in the new era and provided a new scientific and practical way to solve the senior care problems. This paper takes big data, the Internet of Things, cloud computing, and other information technologies as the core, designs and evaluates a cloud platform for intelligent senior care service, and builds a five-layer platform architecture of perception layer, application layer, interface layer, and business layer, the processing layer, and the big data layer. Six major systems realize the cloud platform display of intelligent senior care service: call and service system, data and information management system for the elderly, senior care meal assistance service system, sojourn senior care service system, elderly health management system, and volunteer service system. It effectively meets the needs of the elderly in terms of safety care, emergency assistance, healthy life, spiritual care, etc., and realizes the intelligence, informatization, dataization, and convenience of elderly care.","PeriodicalId":145580,"journal":{"name":"Proceedings of the 5th International Conference on Computer Science and Software Engineering","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116943545","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}
SDN has been proposed to realize flexible network management. Due to the network becomes more complex, multiple controllers are required in SDN. It brings cooperative operation problem among multiple SDN controllers. To solve this problem, common method is to set up a central SDN controller management platform, which increases the construction and operation costs. In this paper, we propose a consensus approach for SDN controllers based on blockchain. Blockchain is a decentralized distributed data management technology. Using this feature, we select the mater controller which has the most abundant resources. The master node completes the production and entry of the block, while the ordinary node accepts the block produced by the master one. To realize this approach, we propose a resource data model of the SDN controller first and a consensus method based on blockchain and this data model.
{"title":"A Consensus Approach for SDN Controllers based on Blockchain","authors":"Jiacong Li, Hang Lv, Bo Lei, Yunpeng Xie","doi":"10.1145/3569966.3570015","DOIUrl":"https://doi.org/10.1145/3569966.3570015","url":null,"abstract":"SDN has been proposed to realize flexible network management. Due to the network becomes more complex, multiple controllers are required in SDN. It brings cooperative operation problem among multiple SDN controllers. To solve this problem, common method is to set up a central SDN controller management platform, which increases the construction and operation costs. In this paper, we propose a consensus approach for SDN controllers based on blockchain. Blockchain is a decentralized distributed data management technology. Using this feature, we select the mater controller which has the most abundant resources. The master node completes the production and entry of the block, while the ordinary node accepts the block produced by the master one. To realize this approach, we propose a resource data model of the SDN controller first and a consensus method based on blockchain and this data model.","PeriodicalId":145580,"journal":{"name":"Proceedings of the 5th International Conference on Computer Science and Software Engineering","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127944646","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}
Yuan Qin, Shaokang Huang, Z. Huang, Xiaoxiao Jiang
The soluble solids content (SSC) of fruits is an important parameter that influences its internal quality. Visible near-infrared (Vis-NIR) spectroscopy is a effective means to detect the internal quality of fruits and vegetables. Measuring samples by instruments generates noise due to environmental factors and machine vibrations, which affects the accuracy of predictions. In this paper, we use standard normalized variables (SNV) and multiplicative scattering correction (MSC) to preprocess the spectral wavelengths, which can effectively reduce the effect of noise. In addition, spectral data contain many redundant variables and useless information, leading to poor prediction of the model. In order to solve this problem, this paper propose a wavelength selection method based on a hybrid strategy of Genetic Algorithm (GA) and Competitive Adaptive Reweighted Sampling (CARS) to screen the effective variables. And the final model is created by partial least squares (PLSR). The GA-CARS model with 84 selected variables has better predictive performance compared to the origin spectrum. In the experiments, samples are obtained from fresh citrus grown in farms around Guilin, and the spectra of citrus are detected in the range of 590 nm-940 nm with a Vis-NIR spectrometer. The experimental results showed that the performance of the prediction model is improved after wavelength screening (RMSEP=0.1581, R2=0.9245). Compared with the traditional algorithm, GA-CARS is an excellent method for screening variables, and the screened wavelengths combined with the model established by PLSR can be a rapid means to detect the SSC of citrus.
{"title":"Non-destructive prediction of soluble solids content in citrus using visible near-infrared spectroscopy","authors":"Yuan Qin, Shaokang Huang, Z. Huang, Xiaoxiao Jiang","doi":"10.1145/3569966.3570086","DOIUrl":"https://doi.org/10.1145/3569966.3570086","url":null,"abstract":"The soluble solids content (SSC) of fruits is an important parameter that influences its internal quality. Visible near-infrared (Vis-NIR) spectroscopy is a effective means to detect the internal quality of fruits and vegetables. Measuring samples by instruments generates noise due to environmental factors and machine vibrations, which affects the accuracy of predictions. In this paper, we use standard normalized variables (SNV) and multiplicative scattering correction (MSC) to preprocess the spectral wavelengths, which can effectively reduce the effect of noise. In addition, spectral data contain many redundant variables and useless information, leading to poor prediction of the model. In order to solve this problem, this paper propose a wavelength selection method based on a hybrid strategy of Genetic Algorithm (GA) and Competitive Adaptive Reweighted Sampling (CARS) to screen the effective variables. And the final model is created by partial least squares (PLSR). The GA-CARS model with 84 selected variables has better predictive performance compared to the origin spectrum. In the experiments, samples are obtained from fresh citrus grown in farms around Guilin, and the spectra of citrus are detected in the range of 590 nm-940 nm with a Vis-NIR spectrometer. The experimental results showed that the performance of the prediction model is improved after wavelength screening (RMSEP=0.1581, R2=0.9245). Compared with the traditional algorithm, GA-CARS is an excellent method for screening variables, and the screened wavelengths combined with the model established by PLSR can be a rapid means to detect the SSC of citrus.","PeriodicalId":145580,"journal":{"name":"Proceedings of the 5th International Conference on Computer Science and Software Engineering","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128003148","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}
{"title":"Panoramic image style transfer technology based on multi-attention fusion","authors":"Xin Xiang, Wujian Ye, Yijun Liu","doi":"10.1145/3569966.3570056","DOIUrl":"https://doi.org/10.1145/3569966.3570056","url":null,"abstract":"","PeriodicalId":145580,"journal":{"name":"Proceedings of the 5th International Conference on Computer Science and Software Engineering","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133234025","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}
Abstract: Laser confocal scanning micro endoscopy has become the focus of current research because of its ability to achieve high-resolution real-time histological diagnosis and certain depth tomography imaging. In the digital communication system of laser confocal scanning micro endoscopy, since the two communication parties are not in the same place, there is a certain transmission delay between the received signal and the transmitted signal. In order to make the two parties work in harmony, a synchronization system must be provided to ensure it. In this paper, the parabola interpolation filter is selected as the interpolation filter, and the Gardner algorithm is selected as the timing error detection module. MATLAB software is used to simulate the digital signal synchronization system of confocal micro endoscope. Finally, we use the signaltap II provided by Quartus II to conduct online logic analysis in FPGA to see whether the results meet the design requirements.
{"title":"Study on Digital Signal Synchronization System of Confocal Micro Endoscope","authors":"Baoqing Zhang, Jing Cao, Li-Yu Daisy Liu","doi":"10.1145/3569966.3569981","DOIUrl":"https://doi.org/10.1145/3569966.3569981","url":null,"abstract":"Abstract: Laser confocal scanning micro endoscopy has become the focus of current research because of its ability to achieve high-resolution real-time histological diagnosis and certain depth tomography imaging. In the digital communication system of laser confocal scanning micro endoscopy, since the two communication parties are not in the same place, there is a certain transmission delay between the received signal and the transmitted signal. In order to make the two parties work in harmony, a synchronization system must be provided to ensure it. In this paper, the parabola interpolation filter is selected as the interpolation filter, and the Gardner algorithm is selected as the timing error detection module. MATLAB software is used to simulate the digital signal synchronization system of confocal micro endoscope. Finally, we use the signaltap II provided by Quartus II to conduct online logic analysis in FPGA to see whether the results meet the design requirements.","PeriodicalId":145580,"journal":{"name":"Proceedings of the 5th International Conference on Computer Science and Software Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131231725","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}
Adaptive Time-Frequency analysis method is of great significance for extracting the fault characteristic frequency of actual complex non-stationary signals. Based on this method, this paper innovatively proposes a multi-channel data acquisition system based on LabVIEW to collect the vibration signal of the bearing test-bed; Through the analysis and comparison of EMD, ITD and LCD algorithms, the characteristics of their algorithms are found. The experimental results show that according to the data collected by LabVIEW multi-channel data acquisition system, the adaptive time-frequency method can be effectively selected to identify the faults of rolling bearings, improve the fault detection rate and practicability of the equipment, and ensure the safe and reliable operation of the equipment.
{"title":"Analysis and research on adaptive Time-Frequency analysis method","authors":"M. Shi","doi":"10.1145/3569966.3569967","DOIUrl":"https://doi.org/10.1145/3569966.3569967","url":null,"abstract":"Adaptive Time-Frequency analysis method is of great significance for extracting the fault characteristic frequency of actual complex non-stationary signals. Based on this method, this paper innovatively proposes a multi-channel data acquisition system based on LabVIEW to collect the vibration signal of the bearing test-bed; Through the analysis and comparison of EMD, ITD and LCD algorithms, the characteristics of their algorithms are found. The experimental results show that according to the data collected by LabVIEW multi-channel data acquisition system, the adaptive time-frequency method can be effectively selected to identify the faults of rolling bearings, improve the fault detection rate and practicability of the equipment, and ensure the safe and reliable operation of the equipment.","PeriodicalId":145580,"journal":{"name":"Proceedings of the 5th International Conference on Computer Science and Software Engineering","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127857790","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}
Aiming at the problems of information overload and insufficient personalized service in multi-service system, a click-through rate prediction model based on LightGBM and DeepFM (LGDF) for multi-service systems is proposed. The LGDF model is based on the framework of LightGBM and DeepFM model. Firstly, LightGBM gradient lifting decision tree is added to the model to perform high-order combination feature transformation and fusion extraction on the features in the original dataset to obtain effective integer result vectors. Then, the integer result vector generated by LightGBM tree prediction is spliced with the original data set to form the new dataset. Finally, the new dataset is used as the input of the DeepFM model to learn the combination relationship of high-order and low-order features between the data. The proposed model is verified on the public dataset Criteo, and the experimental results show that the proposed model LGDF has higher accuracy than other classical models.
{"title":"Click-through rate prediction model based on LightGBM and DeepFM","authors":"Qinghou Qi, Bin Zhao, Wenyin Zhang, Yilong Gao","doi":"10.1145/3569966.3570011","DOIUrl":"https://doi.org/10.1145/3569966.3570011","url":null,"abstract":"Aiming at the problems of information overload and insufficient personalized service in multi-service system, a click-through rate prediction model based on LightGBM and DeepFM (LGDF) for multi-service systems is proposed. The LGDF model is based on the framework of LightGBM and DeepFM model. Firstly, LightGBM gradient lifting decision tree is added to the model to perform high-order combination feature transformation and fusion extraction on the features in the original dataset to obtain effective integer result vectors. Then, the integer result vector generated by LightGBM tree prediction is spliced with the original data set to form the new dataset. Finally, the new dataset is used as the input of the DeepFM model to learn the combination relationship of high-order and low-order features between the data. The proposed model is verified on the public dataset Criteo, and the experimental results show that the proposed model LGDF has higher accuracy than other classical models.","PeriodicalId":145580,"journal":{"name":"Proceedings of the 5th International Conference on Computer Science and Software Engineering","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131207513","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}
Quantum Computers are quickly becoming capable of solving certain tasks substantially faster than classical computers and the promise of quantum-driven advancements in research and economy continues to accelerate the development of quantum technology. However, most software development for quantum computers relies on the tedious manual implementation of quantum circuits on a very low level of abstraction, with tools such as the prominent IBM Qiskit SDK. In 2020, Silq, a quantum language to enable more intuitive and robust quantum development, was presented. While it substantially simplifies the write- and readability of quantum programs, Silq Code can only be run through its simulator on classical hardware. In comparison, Qiskit and its close integration with IBM’s Quantum Experience even enable users to run and evaluate quantum programs on physical quantum hardware. This paper proposes an automatic source-to-source translator for basic Silq Code and the extension of Qiskit by core concepts of Silq’s abstraction layers, such as Quantum Indexing and Quantum Control Flow.
{"title":"Silq2Qiskit - Developing a quantum language source-to-source translator","authors":"Julian Hans, Sven Groppe","doi":"10.1145/3569966.3570114","DOIUrl":"https://doi.org/10.1145/3569966.3570114","url":null,"abstract":"Quantum Computers are quickly becoming capable of solving certain tasks substantially faster than classical computers and the promise of quantum-driven advancements in research and economy continues to accelerate the development of quantum technology. However, most software development for quantum computers relies on the tedious manual implementation of quantum circuits on a very low level of abstraction, with tools such as the prominent IBM Qiskit SDK. In 2020, Silq, a quantum language to enable more intuitive and robust quantum development, was presented. While it substantially simplifies the write- and readability of quantum programs, Silq Code can only be run through its simulator on classical hardware. In comparison, Qiskit and its close integration with IBM’s Quantum Experience even enable users to run and evaluate quantum programs on physical quantum hardware. This paper proposes an automatic source-to-source translator for basic Silq Code and the extension of Qiskit by core concepts of Silq’s abstraction layers, such as Quantum Indexing and Quantum Control Flow.","PeriodicalId":145580,"journal":{"name":"Proceedings of the 5th International Conference on Computer Science and Software Engineering","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129517237","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}
Shao-Luo Huang, Shengyi Qin, Xiaoxiao Jiang, Yi Cao
Customer segmentation is an important approach for customer relationship management, in which many methods are achieved by the Recency, Frequency and Monetary model(RFM) and clustering techniques. However, most methods based on the Recency, Frequency and Monetary model do not consider customer loyalty. In addition, these methods need to use all the historical data when updating the clustering, which has high data storage requirements. In this paper, a clustering method with a time window is proposed to solve these problems. The proposed method is divided into a feature selection stage and a clustering stage. In the feature selection stage, an important factor is considered in an improved Recency, Frequency and Monetary model, called the Length, Recency, Frequency and Monetary model(LRFM). In the clustering stage, a sliding time window is added to intercept the most recent data before the clustering. The proposed method differs from many other methods in that the model takes into consideration a new feature Length to identify customers more accurately, and uses the sliding time window to reduce data storage requirements. Based on the proposed method, the travel customer value analysis is explored on real customer anonymous transaction data. The experimental results show that the proposed method can classify travel customers into different groups effectively. The proposed method has a better clustering performance compared to other baseline algorithms.
{"title":"A travel customer segmentation method based on improved RFM and k-means++","authors":"Shao-Luo Huang, Shengyi Qin, Xiaoxiao Jiang, Yi Cao","doi":"10.1145/3569966.3570085","DOIUrl":"https://doi.org/10.1145/3569966.3570085","url":null,"abstract":"Customer segmentation is an important approach for customer relationship management, in which many methods are achieved by the Recency, Frequency and Monetary model(RFM) and clustering techniques. However, most methods based on the Recency, Frequency and Monetary model do not consider customer loyalty. In addition, these methods need to use all the historical data when updating the clustering, which has high data storage requirements. In this paper, a clustering method with a time window is proposed to solve these problems. The proposed method is divided into a feature selection stage and a clustering stage. In the feature selection stage, an important factor is considered in an improved Recency, Frequency and Monetary model, called the Length, Recency, Frequency and Monetary model(LRFM). In the clustering stage, a sliding time window is added to intercept the most recent data before the clustering. The proposed method differs from many other methods in that the model takes into consideration a new feature Length to identify customers more accurately, and uses the sliding time window to reduce data storage requirements. Based on the proposed method, the travel customer value analysis is explored on real customer anonymous transaction data. The experimental results show that the proposed method can classify travel customers into different groups effectively. The proposed method has a better clustering performance compared to other baseline algorithms.","PeriodicalId":145580,"journal":{"name":"Proceedings of the 5th International Conference on Computer Science and Software Engineering","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124933706","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}
In recent years, the metro passenger flow in big cities has been increasing, and some lines are often crowded and delayed, which brings great pressure to the metro operation and management department. Therefore, it is urgent to build a scientific and effective mathematical model, which can help the metro operation and management department to formulate a reasonable train scheduling plan. This paper provides a new algorithm called APSO. APSO is used to optimize the BP neural network, namely APSO-BP algorithm. Experiments show that APSO-BP has high accuracy for metro passenger flow prediction.
{"title":"Metro Passenger Flow Prediction Based on Optimized BP Neural Network Algorithm","authors":"Fei Xu, Song Gao","doi":"10.1145/3569966.3569995","DOIUrl":"https://doi.org/10.1145/3569966.3569995","url":null,"abstract":"In recent years, the metro passenger flow in big cities has been increasing, and some lines are often crowded and delayed, which brings great pressure to the metro operation and management department. Therefore, it is urgent to build a scientific and effective mathematical model, which can help the metro operation and management department to formulate a reasonable train scheduling plan. This paper provides a new algorithm called APSO. APSO is used to optimize the BP neural network, namely APSO-BP algorithm. Experiments show that APSO-BP has high accuracy for metro passenger flow prediction.","PeriodicalId":145580,"journal":{"name":"Proceedings of the 5th International Conference on Computer Science and Software Engineering","volume":"443 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123383803","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}
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