Reviews from social media are considered as a significant information resource, which is useful for analyzing college students' sentiment and views. Students are eager to express and share their views on web regarding day-to-day activities. That information can be used to understand Chinese college students and their preference. Our research is meaningful in analyzing the psychological processes of students. In order to extract the fundamental student' associated sentiments from those reviews of plain texts, sentiment analysis has emerged and is regarded as a promising technology. In this regard, this paper proposes a novel lexicon model used in college students' domain to exploit semantic relationships between words in natural language text. The sentiment words are initially extracted through lexicon to describe the orientation and the polarity of the attitudes (positive, neutral or negative). Finally, sentiment strength of opinion is calculated and cause event is identified according to the finegrained lexicon. Comparison experimental results on real data from QQ speaking data validate the effectiveness and feasibility of the proposed lexicon model, providing high accuracy levels and low false positive rates. The described lexicon model gives the valuable knowledge to college manager who should detect the students' opinion trends.
{"title":"Sentiment Lexicon for Chinese College Students to Build and Apply","authors":"Di Wu, Jianpei Zhang, Jing Yang","doi":"10.1145/3424978.3425088","DOIUrl":"https://doi.org/10.1145/3424978.3425088","url":null,"abstract":"Reviews from social media are considered as a significant information resource, which is useful for analyzing college students' sentiment and views. Students are eager to express and share their views on web regarding day-to-day activities. That information can be used to understand Chinese college students and their preference. Our research is meaningful in analyzing the psychological processes of students. In order to extract the fundamental student' associated sentiments from those reviews of plain texts, sentiment analysis has emerged and is regarded as a promising technology. In this regard, this paper proposes a novel lexicon model used in college students' domain to exploit semantic relationships between words in natural language text. The sentiment words are initially extracted through lexicon to describe the orientation and the polarity of the attitudes (positive, neutral or negative). Finally, sentiment strength of opinion is calculated and cause event is identified according to the finegrained lexicon. Comparison experimental results on real data from QQ speaking data validate the effectiveness and feasibility of the proposed lexicon model, providing high accuracy levels and low false positive rates. The described lexicon model gives the valuable knowledge to college manager who should detect the students' opinion trends.","PeriodicalId":178822,"journal":{"name":"Proceedings of the 4th International Conference on Computer Science and Application Engineering","volume":"315 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124468620","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}
Yaqing Si, Qingjun Xiao, Jing Su, Sen Zeng, Xiao Hong
This paper aims to construct a data product quality evaluation model for the data circulation market. First of all, this paper established an index system for data product quality evaluation by using multiple dimensions and fully considering the characteristics attached to data sets after production. On this basis, this paper divided all the indexes in the system in to two groups: objective indexes and subjective indexes, then designed reasonable quantitative method for each group according to their own features. With the combination of subjective evaluation and objective measurement, the quality level of data products would be shown in the form of numbers, which is more intuitive.
{"title":"Research on Data Product Quality Evaluation Model Based on AHP and TOPSIS","authors":"Yaqing Si, Qingjun Xiao, Jing Su, Sen Zeng, Xiao Hong","doi":"10.1145/3424978.3425087","DOIUrl":"https://doi.org/10.1145/3424978.3425087","url":null,"abstract":"This paper aims to construct a data product quality evaluation model for the data circulation market. First of all, this paper established an index system for data product quality evaluation by using multiple dimensions and fully considering the characteristics attached to data sets after production. On this basis, this paper divided all the indexes in the system in to two groups: objective indexes and subjective indexes, then designed reasonable quantitative method for each group according to their own features. With the combination of subjective evaluation and objective measurement, the quality level of data products would be shown in the form of numbers, which is more intuitive.","PeriodicalId":178822,"journal":{"name":"Proceedings of the 4th International Conference on Computer Science and Application Engineering","volume":"298 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124258870","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}
We present a convolutional neural network for facial expression recognition based on feature acquisition. The proposed method adopts the structure of dual-channel convolution neural network, the network structure of each channel is designed according to the input sets, the extracted face and the extracted mouth are used as input to two channels simultaneously. Experiments are carried out on two different data sets include JEFFA and FER-2013 to determine the recognition accuracy, and we build a set to test our model, and we compare the generalization performance by using the confusion matrix, then we compared and analyzed the experiment results of recognition accuracy under different facial expressions. Finally, our facial expression recognition system got an accuracy of 82% and 78% respectively, and learning meta face recognition in unseen domains should be researched in the future.
{"title":"Feature Acquisition for Facial Expression Recognition Using Deep Convolutional Neural Network","authors":"Fan Dai, Weihua Li","doi":"10.1145/3424978.3425013","DOIUrl":"https://doi.org/10.1145/3424978.3425013","url":null,"abstract":"We present a convolutional neural network for facial expression recognition based on feature acquisition. The proposed method adopts the structure of dual-channel convolution neural network, the network structure of each channel is designed according to the input sets, the extracted face and the extracted mouth are used as input to two channels simultaneously. Experiments are carried out on two different data sets include JEFFA and FER-2013 to determine the recognition accuracy, and we build a set to test our model, and we compare the generalization performance by using the confusion matrix, then we compared and analyzed the experiment results of recognition accuracy under different facial expressions. Finally, our facial expression recognition system got an accuracy of 82% and 78% respectively, and learning meta face recognition in unseen domains should be researched in the future.","PeriodicalId":178822,"journal":{"name":"Proceedings of the 4th International Conference on Computer Science and Application Engineering","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127208523","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}
Accurate analysis of the patient's heart function, and early diagnosis of myocardial disease can improve the treatment effect and reduce the medical cost significantly. Among the different medical imaging techniques, cardiac magnetic resonance (CMR) has high tissue contrast which is widely used in clinic. However, pro-processing CMR data manually for diagnose is extremely time consuming. To develop an automatic cardiomyopathy recognition algorithm among normal group, hypertrophic cardiomyopathy, and dilated cardiomyopathy group, we employ the CNN and LSTM to extract spatial and motion features. In addition, we propose a motion based auxiliary task to help the main recognition task, without additional annotation. In experiment, compared to C3D [1] and LRCN [2], the proposed method obtains the best performance. Both accuracy and AUC score achieve 0.94.
{"title":"Learning Motion Based Auxiliary Task for Cardiomyopathy Recognition with Cardiac Magnetic Resonance Images","authors":"Jingjing Xiao, Xiangjun Liu, Q. Tao, Jia Chen","doi":"10.1145/3424978.3425122","DOIUrl":"https://doi.org/10.1145/3424978.3425122","url":null,"abstract":"Accurate analysis of the patient's heart function, and early diagnosis of myocardial disease can improve the treatment effect and reduce the medical cost significantly. Among the different medical imaging techniques, cardiac magnetic resonance (CMR) has high tissue contrast which is widely used in clinic. However, pro-processing CMR data manually for diagnose is extremely time consuming. To develop an automatic cardiomyopathy recognition algorithm among normal group, hypertrophic cardiomyopathy, and dilated cardiomyopathy group, we employ the CNN and LSTM to extract spatial and motion features. In addition, we propose a motion based auxiliary task to help the main recognition task, without additional annotation. In experiment, compared to C3D [1] and LRCN [2], the proposed method obtains the best performance. Both accuracy and AUC score achieve 0.94.","PeriodicalId":178822,"journal":{"name":"Proceedings of the 4th International Conference on Computer Science and Application Engineering","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125386766","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}
As the demand for mobile services grows exponentially, the focus on wireless network optimization has been changed from Quality of Service (QoS) for the network to Quality of Experience (QoE) for users. The network optimization research about QoS in the past cannot surely meet the requirements of the users' QoE. Therefore, in this paper, a handover solution is proposed to improve the QoE while considering the QoE balance for a LTE network that provides different services. Compared with other optimization of QoE nowadays, the proposed solution balances and improves the QoE of users. The proposed solution controls handover parameter by running a handover optimization algorithm based on the dynamic particle swarm optimization (DPSO) in a central controller, which finally optimizes the overall QoE and reduces the proportion of users with extremely poor QoE. The simulation results show that the DPSO algorithm ensures the quality of the solution and increases the speed of convergence by nearly twice that of the standard particle swarm optimization algorithm (SPSO). After adopting the DPSO handover solution, the overall QoE of users is increased by 6.22 % and 4.59 % while the variance of users' QoE is decreased by 14.2 % and 22.6 %, compared with the full handover solution and the traditional handover solution respectively. The number of users with QoE less than 1.9 is reduced to 0 with the proposed solution.
{"title":"Improve Quality of Experience of Users by Optimizing Handover Parameters in Mobile Networks","authors":"R. Fang, Gang Chuai, Weidong Gao","doi":"10.1145/3424978.3425031","DOIUrl":"https://doi.org/10.1145/3424978.3425031","url":null,"abstract":"As the demand for mobile services grows exponentially, the focus on wireless network optimization has been changed from Quality of Service (QoS) for the network to Quality of Experience (QoE) for users. The network optimization research about QoS in the past cannot surely meet the requirements of the users' QoE. Therefore, in this paper, a handover solution is proposed to improve the QoE while considering the QoE balance for a LTE network that provides different services. Compared with other optimization of QoE nowadays, the proposed solution balances and improves the QoE of users. The proposed solution controls handover parameter by running a handover optimization algorithm based on the dynamic particle swarm optimization (DPSO) in a central controller, which finally optimizes the overall QoE and reduces the proportion of users with extremely poor QoE. The simulation results show that the DPSO algorithm ensures the quality of the solution and increases the speed of convergence by nearly twice that of the standard particle swarm optimization algorithm (SPSO). After adopting the DPSO handover solution, the overall QoE of users is increased by 6.22 % and 4.59 % while the variance of users' QoE is decreased by 14.2 % and 22.6 %, compared with the full handover solution and the traditional handover solution respectively. The number of users with QoE less than 1.9 is reduced to 0 with the proposed solution.","PeriodicalId":178822,"journal":{"name":"Proceedings of the 4th International Conference on Computer Science and Application Engineering","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115516704","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}
The study aims to explore the safety of ship navigation, in view of 3D (three-dimensional) visualization of navigation mark and of seabed topography. The main contribution lies in two aspects. One is for 3D visualization of aids to navigation, the other is for 3D visualization of seabed topography. From the electronic chart and S-57 data, the shape, color, top mark and luminous characteristics of the navigation mark are extracted. Compared with the previous methods, the simulation on Visual Studio shows that the 3D scene can provide more visual and clear information to the ships. The depth data of electronic chart is extracted and processed, and then the irregular triangular grid is constructed by Delaunay triangular grid method. The two aspects of study, mainly use the corresponding data information to complete the goal of building 3D scene automatically and quickly.
{"title":"3D Visualization of Chart Scenery Based on OSG","authors":"Jinming Song, Xiuwen Liu, Peng Gao","doi":"10.1145/3424978.3425041","DOIUrl":"https://doi.org/10.1145/3424978.3425041","url":null,"abstract":"The study aims to explore the safety of ship navigation, in view of 3D (three-dimensional) visualization of navigation mark and of seabed topography. The main contribution lies in two aspects. One is for 3D visualization of aids to navigation, the other is for 3D visualization of seabed topography. From the electronic chart and S-57 data, the shape, color, top mark and luminous characteristics of the navigation mark are extracted. Compared with the previous methods, the simulation on Visual Studio shows that the 3D scene can provide more visual and clear information to the ships. The depth data of electronic chart is extracted and processed, and then the irregular triangular grid is constructed by Delaunay triangular grid method. The two aspects of study, mainly use the corresponding data information to complete the goal of building 3D scene automatically and quickly.","PeriodicalId":178822,"journal":{"name":"Proceedings of the 4th International Conference on Computer Science and Application Engineering","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128217181","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}
Shuai Ren, Jie Xu, Qianqian Zhang, Lei Shi, Xuemei Lei, Zhuoyi Dan
For the problem of poor robustness of geometric attack based on 3D model information hiding algorithm, an information hiding algorithm based on 3D model spherical segmentation is proposed. The algorithm firstly uses the principal component analysis, spherical coordinate conversion, spherical segmentation, partition sorting, etc. to preprocess the 3D model, calculates the points with large normal vector changes in the three-dimensional partition as the feature points, and matches the feature points according to the amount of secret information to be embedded After wavelet transform, the secret information after the scrambling operation is embedded in the pre-processed carrier to generate a dense three-dimensional model. Experimental results show that the algorithm is invisible and has good robustness to rotation, random noise, heavy mesh, and other common attacks.
{"title":"Information Hiding Algorithm Based on Spherical Segmentation of 3D Model","authors":"Shuai Ren, Jie Xu, Qianqian Zhang, Lei Shi, Xuemei Lei, Zhuoyi Dan","doi":"10.1145/3424978.3425136","DOIUrl":"https://doi.org/10.1145/3424978.3425136","url":null,"abstract":"For the problem of poor robustness of geometric attack based on 3D model information hiding algorithm, an information hiding algorithm based on 3D model spherical segmentation is proposed. The algorithm firstly uses the principal component analysis, spherical coordinate conversion, spherical segmentation, partition sorting, etc. to preprocess the 3D model, calculates the points with large normal vector changes in the three-dimensional partition as the feature points, and matches the feature points according to the amount of secret information to be embedded After wavelet transform, the secret information after the scrambling operation is embedded in the pre-processed carrier to generate a dense three-dimensional model. Experimental results show that the algorithm is invisible and has good robustness to rotation, random noise, heavy mesh, and other common attacks.","PeriodicalId":178822,"journal":{"name":"Proceedings of the 4th International Conference on Computer Science and Application Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128444981","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 the past few years, object detection based on deep learning have attracted attention from more and more organizations and researchers. Compared to one-stage object detection methods, two-stage methods would display a better performance of accuracy and precision. As airplane detection is a basic task in remote sensing images, we propose an airplane-detection method based Faster R-CNN and Feature Pyramid Networks (FPN), with Non-maximum Suppression (NMS) postprocessing. The Faster R-CNN is the most widely used two-stage detection framework, and is still the mainstream box-detection method in many famous detection research platforms like Detectron2 and MMDetection. For the various sizes of airplanes objects, the FPN is used as an excellent technique in recognition systems for detecting objects at different scales. Due to the prominent similarity between different classes of airplanes, the naive two-stage method would yield many duplicate boxes of multiple airplane classes for one object. To improve the recall and precision of the detection model, an NMS Filtering is proposed to prevent the phenomenon of multiple duplicate boxes for one object. The experiment showed that our method is able to accomplish the task in remote sensing for the detection and recognition of airplanes in 24 different classes including helicopter and wing aircrafts, and the NMS postprocessing would have a positive influence on improving the recall and mean average precision (mAP) metrics. The future work would be expanded on improving the precision of classification task.
{"title":"Two-stage Airplane Detection with NMS Filtering in Remote Sensing Images","authors":"Yucheng Song, J. Tian","doi":"10.1145/3424978.3425114","DOIUrl":"https://doi.org/10.1145/3424978.3425114","url":null,"abstract":"In the past few years, object detection based on deep learning have attracted attention from more and more organizations and researchers. Compared to one-stage object detection methods, two-stage methods would display a better performance of accuracy and precision. As airplane detection is a basic task in remote sensing images, we propose an airplane-detection method based Faster R-CNN and Feature Pyramid Networks (FPN), with Non-maximum Suppression (NMS) postprocessing. The Faster R-CNN is the most widely used two-stage detection framework, and is still the mainstream box-detection method in many famous detection research platforms like Detectron2 and MMDetection. For the various sizes of airplanes objects, the FPN is used as an excellent technique in recognition systems for detecting objects at different scales. Due to the prominent similarity between different classes of airplanes, the naive two-stage method would yield many duplicate boxes of multiple airplane classes for one object. To improve the recall and precision of the detection model, an NMS Filtering is proposed to prevent the phenomenon of multiple duplicate boxes for one object. The experiment showed that our method is able to accomplish the task in remote sensing for the detection and recognition of airplanes in 24 different classes including helicopter and wing aircrafts, and the NMS postprocessing would have a positive influence on improving the recall and mean average precision (mAP) metrics. The future work would be expanded on improving the precision of classification task.","PeriodicalId":178822,"journal":{"name":"Proceedings of the 4th International Conference on Computer Science and Application Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124715222","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}
Conditional generative adversarial network are widely used in image translation and many other fields. However, traditional conditional generative adversarial networks have the problem of model collapse. To solve this problem, we proposed a conditional generative adversarial network model based on multiple generators. It uses multiple generators to obtain multiple outputs, and adds a distance constraint between multiple generators to output multimodal results. Experiments on Edges2Shoes and Facade datasets show that the diversity distance index LPILS between generated images can be effectively increased with our method. In addition, it also has good results in coloring application scenarios.
{"title":"Conditional Generation of Adversarial Networks Based on Multiple Generators","authors":"Dunlang Luo, Min Jiang, Jiabao Guo","doi":"10.1145/3424978.3425115","DOIUrl":"https://doi.org/10.1145/3424978.3425115","url":null,"abstract":"Conditional generative adversarial network are widely used in image translation and many other fields. However, traditional conditional generative adversarial networks have the problem of model collapse. To solve this problem, we proposed a conditional generative adversarial network model based on multiple generators. It uses multiple generators to obtain multiple outputs, and adds a distance constraint between multiple generators to output multimodal results. Experiments on Edges2Shoes and Facade datasets show that the diversity distance index LPILS between generated images can be effectively increased with our method. In addition, it also has good results in coloring application scenarios.","PeriodicalId":178822,"journal":{"name":"Proceedings of the 4th International Conference on Computer Science and Application Engineering","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121329498","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 a flow-rack AS/RS, unit-loads to be stored slide from the storage face to the retrieval face driven by the gravity, which lets stored unit-loads follow the first-in-first-out rule in each bin. Consequently, a requested unit-load might be blocked by blocking unit-loads stored in front of it. Blocking unit-loads require extra cost to be removed and restored before retrieving requested ones. Full turnover-based (FTB) storage policy can be employed in flow-rack AS/RS, in which each bin contains the same type of unit-loads to ensure the avoidance of blocking unit-loads when systems request a unit-load. In this paper, the performance of FTB policy is evaluated for the flow-rack AS/RS, which is compared to the in-deep storage policy. Because in-deep storage policy takes a lot of time to deal with blocking unit-loads, we can see whether FTB policy without blocking unit-loads performs better than in-deep storage policy with the same external conditions.
{"title":"Performance Evaluation of Full Turnover-based Policy in the Flow-rack AS/RS","authors":"Meng Zhao, Zhuxi Chen","doi":"10.1145/3424978.3425143","DOIUrl":"https://doi.org/10.1145/3424978.3425143","url":null,"abstract":"In a flow-rack AS/RS, unit-loads to be stored slide from the storage face to the retrieval face driven by the gravity, which lets stored unit-loads follow the first-in-first-out rule in each bin. Consequently, a requested unit-load might be blocked by blocking unit-loads stored in front of it. Blocking unit-loads require extra cost to be removed and restored before retrieving requested ones. Full turnover-based (FTB) storage policy can be employed in flow-rack AS/RS, in which each bin contains the same type of unit-loads to ensure the avoidance of blocking unit-loads when systems request a unit-load. In this paper, the performance of FTB policy is evaluated for the flow-rack AS/RS, which is compared to the in-deep storage policy. Because in-deep storage policy takes a lot of time to deal with blocking unit-loads, we can see whether FTB policy without blocking unit-loads performs better than in-deep storage policy with the same external conditions.","PeriodicalId":178822,"journal":{"name":"Proceedings of the 4th International Conference on Computer Science and Application Engineering","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114208498","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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