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Analysis of learning behaviour based on edX open data 2

Analysis of learning behaviour based on edX open data

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2020 2nd international conference on Electronics and Communication, Network and computer Technology, ECNCT 2020

作者： Feng, Jian Zhao, Yupeng Computer Science AndTechnology Xi'An University Science and Technology Xi'an Shaanxi710600 China

Since 2012, the continuous development of MOOC has triggered new thinking and research in many aspects, and the massive data it generates provides a foundation for learning behaviour analysis and education data research. edX is a new field of Web education jointly developed by Harvard University and MIT integrating educational resources. Based on the first MOOC open data set released by edX, through the use of data analysis methods, the learners in edX are studied from the three aspects of learner type, learner characteristics, and learner behaviour to show the actual situation of MOOC learning. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Open Data

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Metaheuristic Based IDS Using Multi-objective Wrapper Feature Selection and Neural Network Classification 2nd

Metaheuristic Based IDS Using Multi-objective Wrapper Featur...

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2nd international conference on advances in Cyber Security, Aces 2020

作者： Ghanem, Waheed Ali H. M. El-Ebiary, Yousef A. Baker Abdulnab, Mohamed Tubishat, Mohammad Alduais, Nayef A. M. Nasser, Abdullah B. Abdullah, Nibras Al-wesabi, Ola A. Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Kuala Terengganu Malaysia Faculty of Engineering and Faculty of Education-Aden and Saber Aden University Aden Yemen Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Kuala Terengganu Malaysia School of Computing and Technology Asia Pacific University of Technology and Innovation Kuala Lumpur Malaysia Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Parit Raja Malaysia Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Pekan Malaysia National Advanced IPv6 Center Universiti Sains Malaysia Gelugor Malaysia Faculty of Computer Science and Engineering Hodeidah University Al Hudaydah Yemen

ISBN: (纸本)9789813368347

Due to the significant ongoing expansion of computer networks in our lives nowadays, the demand for network security and protection from cyber-attacks has never been more imperative to either clients or businesses alike, which signifies the key role of cyber intrusion detection systems in network security. This article proposes a cyber-intrusion detecting system classification with MLP trained by a hybrid metaheuristic algorithm and feature selection based on multi-objective wrapper method. The classifier, named as HADMLP is trained using a hybridization of the artificial bee colony along with the dragonfly algorithm. A multi-objective artificial bee colony model which is wrapper-based is used for selection of feature. Hence, collective name of the proposed technique referred as MO-HADMLP. For performance evaluation, the proposed method was assessed using ISCX 2012 and KDD CUP 99 datasets. The results of our experiments indicate a significant enhancement to the efficacy of network intrusion detection when compared to other approaches. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Multiobjective optimization

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Exploratory Data Analysis and Data Visualization on Accidental Drug Related Deaths

Exploratory Data Analysis and Data Visualization on Accident...

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Computing and Data Analytics (ICCDA), international conference on

作者： Ezinne Ogwo-Ude Raza Hasan Shakeel Ahmad Salman Mahmood Department of Science and Engineering Solent University Southampton United Kingdom Department of Computer Science Nazeer Hussain University Karachi Pakistan

ISBN: (数字)9798331542573

ISBN: (纸本)9798331542580

The drug overdose epidemic in the United States is rapidly getting worse with substantial associated public health effects. Covering 10,654 cases over a decade (2012–2022), this study analyses an extensive dataset of accidental drug-related deaths in Connecticut. We process and analyze this data using Python and Tableau, we then use LSTM to predict how many people will show up in the designated intervals. The ages of individuals were stated as a mean value 43.52 (SD =12.60) years with a range between 13 and 87 years, bimodally distributed around the mid-30s to mid-50's. Overall, 74.14% were male and 85.48 % white in race/ethnicity. Significant increases were seen in accidental drug-related deaths. The most implicated substances were any opioids, fentanyl (alone or in combination), cocaine alone, heroin and ethanol. Crucially, some 89.05% of the cases had co-abuse with multiple drugs by one person who showed evidence that poly-substance use is commonplace in this community. Most deaths involved fentanyl (309, with a mode at 36 years (229 out of 309 deaths) and r (0.51) associated with ‘any opioid’, the primary cause of death). New Haven, Hartford and Fairfield counties stood out as hotspots for overdoses in geographic analysis. The LSTM model achieved a Root Mean Square Error (RMSE) of 7.25 and a Mean Absolute Error (MAE) of 5.62, predicting a sustained annual increase in deaths over the next three years. This federal and state partnership provides a model for using existing surveillance resources to inform targeted overdose intervention strategies, with an emphasis on the rise of fentanyl positivity among decedents.

关键词： Epidemics Data analysis Correlation Prevention and mitigation Data visualization Opioids Predictive models Market research Public healthcare Long short term memory

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Image data augmentation method based on maximum activation point guided erasure 2

Image data augmentation method based on maximum activation p...

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2nd international conference on advances in computer Technology, Information science and Communications, CTISC 2020

作者： Jiang, Yun Tao, Shengxin Zhang, Hai Cao, Simin Northwest Normal University College of Computer Science and Engineering Lanzhou730070 China

ISBN: (纸本)9781728165011

Deep neural networks usually contain tens to hundreds of millions of orders of learning parameters that provide the necessary representation to solve various visual tasks. But with the increase of the representational ability, the possibility of over-fitting also increase, which bring about poor generalization. In this paper, we propose MA (Maximum Activation point processing) algorithm, a new image data augmentation method which is designed to improve the generalization ability of the model and reduce the risk of overfitting. During the training process, the most discriminative part of the input image is searched for, and the model is driven to search for the supplementary information of the most important feature information by erasing the maximum attention image block. During this process, training images with different occlusion levels are generated as new inputs to the network and the model continues to be trained. The image erasure method based on the maximum activation point guidance only needs to modify the input image, which can effectively improve the robustness of the model to occluded image recognition, and can be integrated with various network structures. The effectiveness of our method is verified on the Cifar10, Cifar100 and Fashion-MNIST datasets. © 2020 IEEE.

关键词： Chemical activation

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Light-Fidelity: Next Generation Wireless Networks-A Survey 2

Light-Fidelity: Next Generation Wireless Networks-A Survey

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2nd international conference on Smart Systems and Inventive Technology, ICSSIT 2019

作者： Kumar, Sudesh Sunanda Arora, Sakshi School of Computer Science Engineering Shri Mata Vaishno Devi University India

ISBN: (纸本)9781728121192

This is the age of speed and everybody requires high speed connectivity to connect with others for sharing useful and necessary information. Presently the most commonly used network is Wi-Fi (IEEE 802.11n) whose maximum speed is around 150mbps. Though this much speed is capable for transmitting lots of information but yet there are hundreds of consumers for whom this is a kind of restriction. For this very reason in 2012, a German Physicist Harald Hans proposed a wireless solution by the name Li-Fi, that is Light Fidelity whose peak transmission rate is 8 Gbps[1]. Light fidelity (Li-Fi) basically refers to an optical networked communication that depends on visible light communication (VLC) to diverge and manage the traffic of mobile data, offering a plethora of advantages when used in an indoor scenario. This article aims to study and analyze the various aspects of Li-Fi and the state-of-the art development made in the field. © 2019 IEEE.

关键词： Light

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Watson-Crick Linear Grammars 2nd

Watson-Crick Linear Grammars

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2nd international conference on Advanced Data and Information engineering, DaEng 2015

作者： Mohamad Zulkufli, N.L. Turaev, S. Mohd Tamrin, M.I. Messikh, A. Department of Computer Science Kulliyyah of Information and Communication Technology International Islamic University Malaysia Kuala Lumpur53100 Malaysia Faculty of Engineering and Natural Sciences International University of Sarajevo Hrasnička cesta 15 Ilidža71210 Bosnia and Herzegovina Department of Information Systems Kulliyyah of Information and Communication Technology International Islamic University Malaysia Kuala Lumpur53100 Malaysia

ISBN: (纸本)9789811317972

In this paper, we define Watson-Crick linear grammars extending Watson-Crick regular grammars Subramanian et al. (CCSEIT’12 proceedings of the second international conference on computer science, science, engineering and information technology 151–156, 2012, [9]) with linear rules, and study their generative power. We show that Watson-Crick linear grammars can generate some context-sensitive languages. Moreover, we establish that the family of Watson-Crick regular languages proper subset of the family of Watson-Crick linear languages but it is not comparable with the family of linear languages. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Automata theory

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The use of Neural Network Modeling for the Selection of Thermophysical Coefficients 2

The use of Neural Network Modeling for the Selection of Ther...

引用

2nd international conference on Electrical, Communication and computer engineering, ICECCE 2020

作者： Platov, Sergey Latypov, Oleg Dema, Roman Kalugina, Olga Institute of Metallurgy Mechanical Engineering and Material Processing Nosov Magnitogorsk StateTehnical University Magnitogorsk Russia National University of Science and Tehnology MISIS Magnitogorsk Russia Computer Sciense and Information Security Nosov Magnitogorsk StateTehnical University Magnitogorsk Russia

ISBN: (数字)9781728171166

ISBN: (纸本)9781728171166

In this work, a simulation model of the thermal state of the work rolls at the hot rolling mill 2000 (m) of Public Joint-Stock Corporation Magnitogorsk iron and steel works (PJSC MMK) is built. A neural network was used as a tool for adjusting the thermophysical transfer coefficients of hot rolling mills. The constructed neural network is a multilayer perceptron, consisting of an input layer, two hidden layers, and an output layer. The neural network is implemented in PyTorch, a scientific computing package based on the interpreted Python programming language. To train the neural network, we used the basic data array obtained from the control system of the hot rolling mill. During industrial experiments, the temperature of the work rolls was measured using HotFind-DXT series thermal imagers developed by SDS. A neural network has been built that allows adapting the thermophysical heat transfer coefficients with an average relative error of 11.7%. A neural network will speed up and simplify the selection of thermophysical coefficients for models of the thermal state of work rolls and adequately assess the current thermal state of work rolls during the rolling process. Using a neural network, a model of the thermal state of work rolls was developed. © 2020 IEEE.

关键词： Hot rolling

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Energy Efficient Designing Approach of Flip-Flops Using 2-Dot 1-Electron QCA 2nd

Energy Efficient Designing Approach of Flip-Flops Using 2-Do...

引用

2nd international conference on Computational Intelligence, Communication, and Business Analytics, CICBA 2018

作者： Ghosh, Mili Mukhopadhyay, Debarka Dutta, Paramartha Department of Computer and System Sciences Visva Bharati University Santiniketan731235 India Department of Computer Science Amity School of Engineering and Technology Amity University Kolkata700156 India

ISBN: (纸本)9789811385773

The most concerned phenomena in present era of digital industry is the dimensional crunch of devices in nanoscale. Quantum-dot Cellular Automata (QCA) is an well known alternative technology to transcend the limitations of CMOS technology. One of the newest structural variant of QCA i.e. 2-dot 1-electron QCA grabbing the attention of the research community due to its energy efficiency. In this present article a design methodology of basic flip-flop circuits such as SR flip-flop, JK flip-flop, D flip-flop and T flip-flop. A detailed energy analysis of the proposed circuits have been carried out to check the energy efficiency and robustness of the proposed circuits. The stability of the proposed circuits have also been analyzed for better assessment of the acceptability of the proposed circuits. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Energy efficiency

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An Approach to DNA Cryptography Using 10Â ×Â 10 Playfair Cipher

An Approach to DNA Cryptography Using 10Â ×Â 10 Playfai...

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2nd international conference on Computational Intelligence, Communication, and Business Analytics, CICBA 2018

作者： Banerjee, Swapnil Roychowdhury, Rajarshi Sarkar, Moumita Roy, Pradipta De, Debashis Department of Computer Science and Engineering Swami Vivekananda Institute of Science and Technology Dakshin Gobindapur P.S.: Sonarpur Kolkata700145 India Department of Computer Science and Engineering Maulana Abul Kalam Azad University of Technology BF-142 Sector-1 Salt Lake CityKolkata700064 India Department of Physics University of Western Australia M013 35 Stirling Highway Crawley PerthWA6009 Australia

ISBN: (纸本)9789811385803

Nowadays, sensitive information is conveyed over public communication medium, where data security is an enormous problem and cryptography is the ideal mechanism to handle it. DNA cryptography is a modern cryptographic way to conceal data in terms of DNA. The rudimentary purpose of this cipher is to enhance the security features of classical playfair and making it more robust by applying DNA encoding. The duplets, in the original message are considered as a single unit and transformed into respective medialcipher text duplet. DNA encoding with interweaving step is applied on medialcipher text. Therefore, the terminalcipher text is a DNA sequence of data, which leaves a very thin relation between the original message and terminalcipher text, and makes this encryption technique more stochastic. Further, some performance analysis of the proposed cipher has been explained to get a clear view about the method. © 2019, Springer Nature Singapore Pte Ltd.

关键词： DNA

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A Blackboard Sharing Mechanism for Community Cyber Threat Intelligence Based on Multi-Agent System 1

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2nd international conference on Machine Learning for Cyber Security, ML4CS 2019

作者： Lin, Yue Wang, He Yang, Bowen Liu, Mingrui Li, Yin Zhang, Yuqing School of Cyber Engineering Xidian University Xi’anShaanxi China National Computer Network Intrusion Protection Center University of Chinese Academy of Sciences Beijing China

ISBN: (数字)9783030306199

ISBN: (纸本)9783030306182

In the process of increasing cybersecurity attack and defense confrontation, there is a natural asymmetry between the offensive and defense. The Cyber Threat Intelligence (CTI) sharing mechanism is an effective means to improve the emergency-response ability of the protection party. However, currently, there are no effective sharing schemes in the community network to facilitate cross-sector threat intelligence sharing. This paper presents a collaborative threat intelligence sharing mechanism based on the blackboard model, which can be used to identify potential risks, prevent cyber attacks at an early stage, and facilitate community incident response. According to the China National Standard "Cyber security threat information format", we divide threat intelligence sharing into routine and attack-specific threat intelligence sharing. Also, we design an attack-specific threat intelligence sharing module based on the blackboard model and describe the sharing process. Finally, we design the blackboard monitoring mechanism as a Multi-Agent System (MAS) to realize many tasks in the sharing process. Our scheme is illustrated by several CTI sharing scenarios in the community. © 2019, Springer Nature Switzerland AG.

关键词： Multi agent systems

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