{"title":"Measuring the efficiency of highly funded scientists in China based on the data envelopment analysis","authors":"Keyu Xiang, Haiming Liang, Zhaoxia Guo, Yucheng Dong","doi":"10.1109/ICIST52614.2021.9440617","DOIUrl":"https://doi.org/10.1109/ICIST52614.2021.9440617","url":null,"abstract":"Since the competition in the scientific community is becoming increasingly fierce, measuring the research performance of highly funded scientists is growingly critical for relevant management authorities to make effective policies in scientific research and development. However, little quantitative analysis has focused on this issue. To facilitate the research in this area, we first construct a dataset containing both the funding inputs and the research paper outputs of highly funded scientists in China. Then, instead of directly summing quantitative indicators, in this paper, we measure the efficiency of highly funded scientists in China based on the data envelopment analysis models. We show that we can grade highly funded scientists into several grades and present their scores on attractiveness or progress to other grades. The gradual learning path for less efficient scientists is also provided. These patterns of highly funded scientists may be beneficial for management authorities to make effective policies.","PeriodicalId":371599,"journal":{"name":"2021 11th International Conference on Information Science and Technology (ICIST)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133405439","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":"Mutual Attention Graph Neural Network Based on Joint Representation of Nodes and Reviews for Recommendation","authors":"Yafei Song, Guoyong Cai","doi":"10.1109/ICIST52614.2021.9440598","DOIUrl":"https://doi.org/10.1109/ICIST52614.2021.9440598","url":null,"abstract":"Recently, recommendation system have achieved good results by applying graph neural network to user-item inter-action graph. However, current graph neural network mainly deals with structured data and cannot deal with unstructured re-view text well. Item reviews are a unique way for users to choose to purchase the item. Therefore, combining a user-item interaction graph with related review text will obtain better recommendation performance. At the same time, most of the recommendation methods that have been proposed simply concatenate the representations from different modalities to make predictions. This can-not take advantage of the information from different modalities. To solve these problems, we propose a Mutual Attention graph neural Network (MAN) for personalized recommendation. MAN first extracts user/item node representation on user-item interaction graph through node feature extraction module, and extracts user/item review text representation through review feature ex-traction module. Then a mutual attention module is used to correlate node representation and review text representation, so as to capture the correlation between the node representation and the review text representation during the training process. Experimental results on three real-world datasets show MAN is better than the state-of-the-art personalized recommendation method.","PeriodicalId":371599,"journal":{"name":"2021 11th International Conference on Information Science and Technology (ICIST)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124234447","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":"Molecular Diagnosis: And using Ubiquitous Transcription Factor and MAPK to Recover Thyroid Cells of Hyperthyroidism and Heart","authors":"A. Junejo, Nauman Ullah Gilal, Xiang Li","doi":"10.1109/ICIST52614.2021.9440612","DOIUrl":"https://doi.org/10.1109/ICIST52614.2021.9440612","url":null,"abstract":"This study sought to explore the Molecular Diagnosis (MD) mechanism and Targets of the Treatment effects on cardiovascular disease (CVD) by studying the regulatory effects of NF – κB and MAPK triggered in hyperthyroidism. Researchers have proposed a new MD paradigm to resolve this problem, which combines Nanoparticles-Medicine (NPs-M) with synthetic biology tools to provide biocomputing equipment redesign. The recombinant adenovirus of the TSHR-A subunit was injected into the anterior tibial muscle of BALB/C mice to create a model. The hyperthyroidism of those mice was taken to ensure a primary cell. Immunohistochemistry, techniques, and divisions into the groups and the medicated serum group were identified as thyroid cells, in terms of excess thyroid hormone affects CVD. These triggered pathways induce the content and expression of hyperthyroidism ICAM-1, cytokines IL-6, and CXCL10. In comparison with the model group, the medicated serum group had a significant callback effect, and the medicated serum had a significant callback effect on IL-6 levels. These results demonstrated that the regulatory effect on MAPK, NF – κB, and other cell triggered pathways in CVD and graves’ disease (GD) hyperthyroidism. We speculate that it can regulate the occurrence and development of targets of the treatment effects on Disease by inhibiting the activation of MAPK and NF – κB cell pathways and the expression of downstream cytokines. Furthermore, the possible direction of the MAPK and NF – NF – B pathway in soleus heart failure rats.","PeriodicalId":371599,"journal":{"name":"2021 11th International Conference on Information Science and Technology (ICIST)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115061201","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":"PointDet: An Object Detection Framework Based On Human local Features In The Task Of Identifying Violations","authors":"Yudi Tang, Bing Wang, Wangli He, Feng Qian","doi":"10.1109/ICIST52614.2021.9440553","DOIUrl":"https://doi.org/10.1109/ICIST52614.2021.9440553","url":null,"abstract":"Object detection algorithms play an important role in the field of violation detection. However, small target detection is full of challenges in scenes related to human. The relationship between objects is usually not considered in object detection algorithms, which will make the model over relay on the high-order features and not make full use of local features. To address this issue, a novel framework named PointDet is proposed to learn local features which optimizes the detection effect of small targets in chemical plants. Since most of the targets to be detected in our dataset are highly correlated with human, human local features are used when designing the framework. First, we use a trained pose estimation model to extract local key point features. However, if local features are used directly, the relationship between them cannot be fully considered. Based on this situation, we have designed the one-vs-others module and the adaptive-graph-convolution module to reconstruct local features. In addition, for the output layer, the most challenging problem is how to better detect small targets. In our task, various small objects such as gloves, goggles, etc. have an obvious positional relationship with the local features of human body. In the output layer, we have designed a head attention module to make full use of this situation to optimize the small target detection problem. Specifically, our framework significantly outperforms state-of-the-art by 7.8 AP scores on field work dataset in chemical plants.","PeriodicalId":371599,"journal":{"name":"2021 11th International Conference on Information Science and Technology (ICIST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131326367","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":"Finite-time tracking consensus in probability for multi-agent system with noises and time delay","authors":"Mingyan Tuo, Fenglan Sun, Feng Wang, Hao Li","doi":"10.1109/icist52614.2021.9440641","DOIUrl":"https://doi.org/10.1109/icist52614.2021.9440641","url":null,"abstract":"This paper studies the finite-time tracking consensus in probability of multi-agent systems with noises and time delay. By using the method of pinning control and observer, the system both with and without the leader as the root of a spanning tree is considered. According to algebraic graph theory, stochastic Lyapunov stability theory and control theory, sufficient conditions for the tracking consensus are given. Numerical simulations are given to verify the effectiveness of the main results.","PeriodicalId":371599,"journal":{"name":"2021 11th International Conference on Information Science and Technology (ICIST)","volume":"188 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121075699","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}
Yao Xiao, Xiangguang Dai, Xiangqin Dai, Nian Zhang
{"title":"Truncated Cauchy for Robust fast supervised discrete hashing","authors":"Yao Xiao, Xiangguang Dai, Xiangqin Dai, Nian Zhang","doi":"10.1109/ICIST52614.2021.9440614","DOIUrl":"https://doi.org/10.1109/ICIST52614.2021.9440614","url":null,"abstract":"We propose a novel data-dependent hashing algorithm named Truncated Cauchy for Robust fast supervised discrete hashing (RFSDH) for robust subspace learning. In this paper, a Truncated Cauchy loss is proposed to measure the factorization error, which can handle outliers by truncating large errors. The proposed method can inhibit the unreliable binary codes, which generate the optimal binary codes. Our method can be expressed as a mixed-integer optimization problem, which can be to solve by iterative discrete cyclic coordinate descent. RFSDH method accomplishes outperform other hashing learning methods in image retrieval effect on two large scale datasets.","PeriodicalId":371599,"journal":{"name":"2021 11th International Conference on Information Science and Technology (ICIST)","volume":"46 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125676217","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":"A review of intelligent optimization algorithm applied to unmanned aerial vehicle swarm search task","authors":"Zhu Qiming, Wu Husheng, Fu Zhaowang","doi":"10.1109/ICIST52614.2021.9440608","DOIUrl":"https://doi.org/10.1109/ICIST52614.2021.9440608","url":null,"abstract":"Collaborative search is one of the key application fields of UAV swarm, Efficient and accurate algorithm is very important to complete the task of UAV swarm search, and the dynamic and real-time uncertainty of unmanned aerial vehicle swarm search task makes the problem very difficult. Therefore, in the past few years, a large number of scholars have shown strong interest in the problem of UAV swarm search task. With the rapid development of computer technology and Intelligent optimization algorithm, many Intelligent optimization algorithm have been proposed to solve this problem. However, the research on cooperative control and search algorithm is still not comprehensive, and there is a lack of induction and summary of recent research results. The purpose of this paper is to introduce the mathematical model of the search task and give a comprehensive review of the intelligence algorithms used in the swarm search task in recent years and their improvement. In addition, the results and efficiency of each algorithm to solve UAV search tasks are compared, and the advantages and disadvantages of different swarm intelligence algorithms applied to UAV swarm search tasks are summarized and summarized, so as to provide useful reference for UAV swarm to complete search tasks in the future.","PeriodicalId":371599,"journal":{"name":"2021 11th International Conference on Information Science and Technology (ICIST)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125087130","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":"A Data-Driven Storage Assignment Strategy for Automated Pharmacy","authors":"Lei Hao, Hongfeng Wang, Q. Yan","doi":"10.1109/ICIST52614.2021.9440600","DOIUrl":"https://doi.org/10.1109/ICIST52614.2021.9440600","url":null,"abstract":"Automated pharmacy (AP) with random storage location assignment (RSLA) strategy has been widely applied in large hospitals and retail pharmacies. In this paper, an integrated optimization problem of storage location assignment (SLA) and robot arm path planning (RAPP) is considered. For the trade-offs, a Hungarian method (HM)-based storage location assignment (HMSLA) method is proposed for further improving the operation efficiency of AP. Two phases are involved in the proposed method. At phase one, AP is divided into four areas based on BP neural network, and then medicine storage area and specific location are determined through data mining of drug delivery frequency and common combinations. At phase two, HM is applied for optimal scheduling of dispensing multiple medicines. Numerical studies show the proposed method outperforms significantly the traditional RSLA strategy.","PeriodicalId":371599,"journal":{"name":"2021 11th International Conference on Information Science and Technology (ICIST)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122744014","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":"Solving the Travelling Salesman Problem Based on Collaborative Neurodynamic Optimization with Discrete Hopfield Networks","authors":"Hongzong Li, Jiasen Wang, Jun Wang","doi":"10.1109/ICIST52614.2021.9440588","DOIUrl":"https://doi.org/10.1109/ICIST52614.2021.9440588","url":null,"abstract":"This paper addresses the travelling salesman problem (TSP) based on collaborative neurodynamic optimization (CNO). In the CNO approach to TSP, a population of discrete Hopfield networks are employed for searching local optimal solutions and repeatedly reinitialized by using the particle swarm optimization rule towards a global optimal solution. Experimental results for solving four TSP benchmarks are reported to substantiate the efficacy of the CNO approach.","PeriodicalId":371599,"journal":{"name":"2021 11th International Conference on Information Science and Technology (ICIST)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121864053","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":"2D Grid map for navigation based on LCSD-SLAM","authors":"Yan Zhou, Biye Li, Dongli Wang, Jinzhen Mu","doi":"10.1109/ICIST52614.2021.9440650","DOIUrl":"https://doi.org/10.1109/ICIST52614.2021.9440650","url":null,"abstract":"This paper establishes a 2D grid map based on the semi-direct method, which can be used for navigation, sweeping robot and other applications. In order to implement the method with the help of the ROS platform, on the monocular semi-direct LCSD-SLAM method, after obtaining the key frames, a 2D grid map is constructed. Most of the current 3D to 2D map conversion research uses octrees for conversion, but we have proposed a threshold-based method, which is based on a monocular semi-direct method. After LCSD-SLAM obtains the key frame, through calculation, the 3D map is converted into a 2D grid map in real time. The A* path planning algorithm can be used to navigate in the 2D grid map. Experimental results show that the proposed method can successfully establish a 2D grid map and can be effectively applied in subsequent navigation.","PeriodicalId":371599,"journal":{"name":"2021 11th International Conference on Information Science and Technology (ICIST)","volume":"197 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124927505","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}