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An efficient statistical method for evaluating online teaching quality 21

An efficient statistical method for evaluating online teachi...

引用

Proceedings of the 2021 4th international conference on Algorithms, computing and Artificial Intelligence

作者： Sumei Zhang Qiujuan Tong School of Science Xi'an university of Post and Telecommunications China

ISBN: (纸本)9781450385053

the purpose of this study is to provide an efficient statistical analysis method to evaluate online teaching quality. A comprehensive evaluation model is established based on factor analysis theory. Fewer key indexes to summarize information in various aspects are extracted, through which comprehensive scores of every teacher evaluated are obtained. As an illustration, evaluated data from twenty teachers of Xi'an university of Post and Telecommunications is analyzed and modelled by the presented method and SPSS software. the results from the example show that the proposed method is efficient.

关键词： Evaluation Factor analysis Teaching quality SPSS Online teaching

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Application of Capsule Network to Tablet Identification 21

Application of Capsule Network to Tablet Identification

引用

Proceedings of the 2021 4th international conference on Algorithms, computing and Artificial Intelligence

作者： Wenliang He Minling Zhu Computer School Beijing Information Science & Technology University China

ISBN: (纸本)9781450385053

To address the problem of pill defect recognition, we propose to apply capsule neural network for pill defect recognition. the effects of dynamic routing iteration rounds and different compression function constant term schemes on the performance of the capsule neural network are investigated in the context of small data sets, and the model effects are verified experimentally. the experimental results show that both the number of dynamic routing iteration rounds and different compression function constant term schemes can affect the performance of the capsule neural network, and it is essential to choose an appropriate scheme in the process of training the model. the capsule neural network is found to be suitable for the field of pill defect recognition through *** CONCEPTS • computing methodologies∼Visual content-based indexing

关键词： capsule network image recognition Deep learning dynamic routing pill identification

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Scenario-Driven Device-to-Device Access Control in Smart Home IoT

Scenario-Driven Device-to-Device Access Control in Smart Hom...

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IEEE international conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA)

作者： Mehrnoosh Shakarami James Benson Ravi Sandhu Department of Computer Science Institute for Cyber Security (ICS) & NSF Center for Security and Privacy Enhanced Cloud Computing (C-SPECC) University of Texas at San Antonio San Antonio US

the Internet of things (IoT) has been widely integrated in people's everyday lives. As an infrastructure of connected heterogeneous devices, IoT has not yet achieved the seamless integration of device-to-device collaboration which is necessary for real-life home automation. Smart home IoT devices expect to exchange their collected data or status in certain circumstances, in spite of their heterogeneity, viz. working with different communication protocols, IoT platforms, middleware, data and semantics. Deploying appropriate access control models and mechanisms is of utmost importance as any unauthorized access to data could have a cascading violation of privacy, safety and security of users. In this work, we propose a novel device-to-device access control paradigm in the smart home IoT. Our approach relies on message passing as the paradigm for device-to-device interactions. We further introduce actions and scenarios reflecting the chain of events in the smart home context, which facilitates scenario-driven attribute-based access control. Each scenario is triggered by triggering events, based on previously set administrative definitions. We define totally ordered sets of triggering events using priorities to enable conflict resolution for devices which may run into conflicting commands delivered though messages in different ongoing scenarios. the viability of the proposed approach is substantiated via a formal model and an enforcement architecture, backed up by a proof-of-concept implementation which affirms a trade-off between required authorization and efficacy. Potential future challenges are explored in the context of smart home IoT platforms.

关键词： Authorization Privacy Protocols Message passing Computational modeling Semantics Smart homes

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Auto-generating Textual data Stories Using data science Pipelines 21

Auto-generating Textual Data Stories Using Data Science Pipe...

引用

Proceedings of the 2021 4th international conference on Algorithms, computing and Artificial Intelligence

作者： Ruilin Wang Somayajulu Gowri Sripada Nigel Beacham Computer science University of Aberdeen UK

ISBN: (纸本)9781450385053

Understanding a dataset directly is challenging but transforming the results of data analysis into data stories could help people build mental models and understand the dataset easily. In this paper, we present a new framework for data-to-text NLG to generate data stories for specific personas. In order to understand the feasibility of this method and if the human generated story is consistent with the story generated by the data science pipelines, we present two experiments: a data story study with 3 financial experts, 4 Ph.D. students, and 20 Amazon Mechanical Turk workers, which offers several data stories generated by humans; and a validation study involving 39 Amazon Mechanical Turk workers who conducted usability and understandability assessments for 9 high-quality data stories, written by humans and machine. We conduct a qualitative analysis of human-written data stories to determine what people consider when writing data stories and if the human generated story is consistent with the one generated by the data science pipeline. the experimental results show that readers comprehend machine-written data stories as well as they comprehend human-written data stories.

关键词： NLP data science data Storytelling data sensemaking

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Mobile terminal and Inspection Station Management System

Mobile terminal and Inspection Station Management System

引用

Advances in computing, Communication Control and Networking (ICAC3N), international conference on

作者： Bukkapatnam Sai Kamal Er. Nitika Kapoor Department of Computer Science and Engineering Chandigarh University Mohali Punjab India

Time and Money are the two things which are ruling the world. But there are many other things that have been focused on saving, such as deforestation, which is caused by the killing billions of trees, we are proposing an application that can save a lot of time, money, and paper. It is an online discovery platform where customers can find the menu of a restaurant or the list of products of the shop which they visit, place orders and pay online directly and collect the items by showing the bill generated on our mobile. Internet and mobile application are the main channels utilized for the entire cycle for clients to put in a request and furthermore to choose the appropriate shop. this can save tons of paper by generating bills online. Once the application is launched the complete data will be updated when the stock arrives, later it keeps a calculation and notifies the seller when the item is going to finish. the buyer can check the items available in the shop from his home itself, place an order, and a bill will be automatically generated. So, until he arrives at the shop the item will be perfectly packed hence the person can show the bill which is generated in his mobile and get his item from the counter. this purposed work facilitates both buyers and sellers. the buyer can check the menu and also the special deals provided by the sellers to get a maximum discount. But in the case of the seller, the application does the entire work like Billing, making a List of Items Left and Sold, and maintain the complete database. In restaurants, it directly gets an order from Costumer sitting at the table and generates the bill in the application. So, the seller can have limited staff working which can save a lot of money. Due to the technology, the major crowd issue which our country is facing can be reduced in just a few months of awareness. Hence this single application can save a lot of Time, Money, Paper, and also resolve the major crowd issue.

关键词： Social networking (online) Law Multimedia Web sites Media Inspection Routing Mobile applications

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BERT-based models’ impact on machine reading comprehension in Hindi and Tamil

BERT-based models’ impact on machine reading comprehension ...

引用

Advances in computing, Communication Control and Networking (ICAC3N), international conference on

作者： Shailender Kumar Deepak Department of Computer Science Delhi Technological University New Delhi India

ISBN: (数字)9781665474368

ISBN: (纸本)9781665474375

"Multilingual Machine Comprehension" is a QA sub-task that comprises citing an answer to a question from a context, even if that answer written in a separate language from the excerpt itself. A lot of models have been trained to answer the question from a given short context which is a limitation of MRC, few models are considering this problem and adapting to handle the large input context to make the MRC more accessible and applicable to open domain scenarios. In this study, we examine Multilingual Representations for Indian Languages (MuRIL), rebalanced multilingual BERT (RemBERT), and XLM-RoBERTa, which are all BERT-based deep learning models. We trained these models to work on multilingual MRC particularly for two of the most used Indian languages Hindi and Tamil the datasets utilized in this study are freely available. the results of our research reveal that RemBERT outperformed other BERT-based deep learning models. For the dataset employed, the model received an F1 score of 84.58, an Exact Match of 74.05, and a Jaccard Index of 0.81.

关键词： Deep learning Adaptation models Computational modeling Bit error rate Transformers data models Context modeling

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Expression of Concern for: Text Classification Using Feature Extraction and Classification Model

Expression of Concern for: Text Classification Using Feature...

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Advances in computing, Communication Control and Networking (ICAC3N), international conference on

作者： Anirudh Rana Vishal Bharti Department Of Computer Science and Engineering Chandigarh University Gharuan

ISBN: (数字)9781665474368

ISBN: (纸本)9781665474375

Sentiment analysis represents context-based text mining that classifies and abstracts particular information from the source data, and helps to interpret people's feelings. It adopts the NLP approach to classify people's opinions regarding goods or feedback. Sentiment analysis handles people's opinion and behavior in the context of feelings and attitudes concerning an episode or incidence. there are many domains that use opinion mining widely such as commercial goods review, social media study and film evaluation and so on. Semantic analysis provides major support in building recommendation frameworks. User provides textual feedback such as web-based reviews, remarks or responses on social networking and business sites. Machine learning is a common approach used for classification. this project devises a nascent methodology through the integration of dissimilar frameworks. this work applies Random Forest as a feature extraction method for taking out crucial features of the data suite. the K-mean clustering is enforced which can cluster similar type of features and in the last voting classifier is applied. Voting classifier consists of LR, KNN, SVM models. Python is the tool used in this work for the implementation of the devised methodology and evaluates new methodology with respect to some global performance indices.

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RWRel: A fast training framework for random walk-based knowledge graph embedding 21

RWRel: A fast training framework for random walk-based knowl...

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Proceedings of the 2021 4th international conference on Algorithms, computing and Artificial Intelligence

作者： Hui Zhang Da-Gao Duan Qiu-Li Zhang Department of Computer Science and Engineering Beijing Technology and Business University China Department of International Economics and Management Beijing Technology and Business University China

ISBN: (纸本)9781450385053

With the development of typical graph data scenarios such as social networks and recommender systems, the size of knowledge graphs is growing. In recent years, large-scale knowledge graphs have posed a challenge in terms of fast training of knowledge graph representation model when applied. the article proposes a fast training framework for random walk-based embedding of knowledge graphs (RWRel), which contains a random walk strategy based on relational paths and a relational encoding that introduces subject-object embeddings to model the subject-object semantics of relations in knowledge graphs. the experimental results show that the RWRel framework is effective in improving the speed and maintaining the performance of the representation learning method.

关键词： representation learning random walk knowledge graphs

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Testability Evaluation by Multi-sources Bayes Method Applied in Torpedo Weapon System with Improved Jaccard Similarity 21

Testability Evaluation by Multi-sources Bayes Method Applied...

引用

Proceedings of the 2021 4th international conference on Algorithms, computing and Artificial Intelligence

作者： Kangkang Dou Mengyuan Zhan Zhen Li Xiankang Chen Department of Information Technology Research Jiangsu Automation Research Institute China School of Electronics and Information Jiangsu University of Science and Technology China 13th Research Office Information Center of China State Shipbuilding Corporation China

ISBN: (纸本)9781450385053

Aiming at the small sample problem in the testability evaluation of complex equipment systems, this paper takes the application of a torpedo combat system as an example. Based on the Bayes theory, a hybrid pre-information weighted fusion based on the improved Jaccard coefficient to consider the similarity of historical models is proposed. this method not only solves the problem of "small samples" of complex equipment testability data, but also avoids the risk of field data being overwhelmed by the traditional Bayes method due to the different overall characteristics of multi-source information and field data. Comparative analysis of examples shows that the method used in this paper is more accurate and reasonable in test evaluation than the classical evaluation method and traditional Bayes evaluation method, and has better engineering application value.

关键词： Torpedo combat system Small sample Bayes theory Testability evaluation Multi-sources information

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Clutter Environment Perception Based on Prototypical Network 2021

Clutter Environment Perception Based on Prototypical Network

引用

2021 4th international conference on computing and Big data

作者： Xiangfeng Qiu Weidong Jiang Xinyu Zhang Kai Huo College of Electronic Science and Technology National University of Defense technology China

ISBN: (纸本)9781450387194

Clutter environment perception is the basic function of the cognitive radar system, which provides prior information for the subsequent transmitted waveform optimization and adaptive processing of the received signal. In a typical airborne or missile-borne platform, in order to respond quickly to the environment of the high-value target to be detected, the radar only has a short observation window length and cannot obtain enough data for clutter environment perception, leading to a problem of clutter environment perception under the condition of few data. Aiming at the problem of insufficient clutter environment data, this paper proposed a clutter environment perception method based on prototypical network. It employed the High-Resolution Range Profile of wideband radar as the recognition data, and first used data in the training set to calculate the prototypes corresponding to different clutter environment features. then, the distances between the features of data in the testing set and the different prototypes was used to realize the perception of the clutter environment. the measured data on microwave anechoic chamber showed that the methods used in this paper can obtain effective perception results for the three typical natural environments of grassland, cement, and asphalt.

关键词： High-Resolution Range Profile environment perception prototypical network radar clutter

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