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A Data-Driven Government Response Analysis to COVID-19 in Delta Variant Stage based on FCM-DID Model 6

A Data-Driven Government Response Analysis to COVID-19 in De...

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6th international conference on computing and Big Data, ICCBD 2023

作者： Wu, Ruibing Wong, Johnston Hong-Chung Peng, Xiaoling BNU-HKBU United International College Department of Statistics and Data Science Zhuhai China United International College Faculty of Humanities and Social Sciences BNU-HKBU Zhuhai China United International College Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application or Data Science BNU-HKBU Zhuhai China

ISBN: (纸本)9798350317008

Aimed to provide insight into the global trend of COVID-19 during the Delta variant stage and offer recommendations for effective epidemic prevention policies. In this study, we propose a novel data-driven causal inference model combining fuzzy c-means (FCM) clustering and difference-in-difference (DID) for multiple time series data. Based on the FCM clustering, a set of panel data with parallel trends can be obtained for further DID analysis. By comparing the change in the outcome variable between the treatment and control groups within each cluster, before and after the intervention, the causal effect of each cluster on the outcome variable is estimated. In government response analysis to COVID-19, the daily updated data of 196 countries all over the world during the transition phase from the outbreak of the SARS-CoV-2 Delta variant to the discovery of Omicron was collected. Application of our method shows that adopting restrictions on internal movement policies had a substantial impact on preventing the spread of the pandemic. the FCM-DID approach we proposed is useful for identifying and comparing the effects of policies on the outcome of different groups, thus can well evaluate the effectiveness of implemented policies and provide valuable guidance for decision-making in future public health crises. © 2023 IEEE.

关键词： Time series

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Abnormal Industrial Control Protocol Identification Based on Feature Boosting

Abnormal Industrial Control Protocol Identification Based on...

引用

2023 international conference on Algorithms, computing and Data Processing, ACDP 2023

作者： Wang, Shaojie Cao, Gang Wan, Jiarong Qi, Bin Wang, Yishuo The 6th Research Institute China Electronics Corporation Beijing China

ISBN: (纸本)9798350326680

the development of the Internet has brought great convenience to people's life, but it has also brought potential dangers, such as zero-day vulnerabilities and DoS attacks. Abnormal industrial control protocol identification is an important part of industrial control security. It detects whether the behavior violates the security policy by collecting some key point data in the computer network and system for analysis. Aiming at the increasingly stealthy network attacks, we explore a feature generation method and several classification algorithm are applied to identify. In the feature extraction stage, we used a technique called feature boosting and generated new feature set, and then we used a variety of classification models to identify the new feature set, including Naive Bayes, KNN, SVM, Knowledge Distillation. For new feature set, the above classification models are applied and perform well. Our work demonstrates that anomalous control protocol can be effectively identified even with commonly used classification models after employing feature boosting techniques, which provides a potential approach for industrial control Protocol recognition. © 2023 IEEE.

关键词： Denial-of-service attack

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Deep Reinforcement Learning-based Obstacle Avoidance for Robot Movement in Warehouse Environments 6

Deep Reinforcement Learning-based Obstacle Avoidance for Rob...

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6th IEEE international conference on Civil Aviation Safety and Information Technology, ICCASIT 2024

作者： Li, Keqin Chen, Jiajing Yu, Dezhi Dajun, Tao Qiu, Xinyu Lian, Jieting Ji, Ryan Zhang, Shengyuan Wan, Zhenyu Sun, Baiwei Hong, Bo Ni, Fanghao Han, Jiaqi Ama University Department of Computer Science Quezon Philippines Courant Institute New York University 251 Mercer St New YorkNY10012 United States University of California Berkeley University Avenue and Oxford St School of Information BerkeleyCA94720 United States Carnegie Mellon University Master of Science in Mechanical Engineering School of Engineering 5000 Forbes Avenue PittsburghPA United States Northeastern University College of Engineering Seattle United States School of Professional Studies New York University Master of Science in Database Technology 50 West 4th Street New YorkNY United States Cornell University College of Engineering 616 Thurston Ave IthacaNY14853 United States Cornell University Master of Professional Science in Applied Statistics-Data Science College of Computing and Information Science 616 Thurston Ave IthacaNY United States Independent Researcher Beijing China University of California Irvine Master of Computer Science Donald Bren School of Information and Computer Sciences 510 Aldrich Hall IrvineCA United States Northern Arizona University School of Informatics Computing and Cyber Systems FlagstaffAZ United States Shanghai Institute of Technology Shanghai China

ISBN: (纸本)9798350389418

this paper proposes a deep reinforcement learning based on the warehouse environment, the mobile robot obstacle avoidance Algorithm. Firstly, the value function network is improved based on the pedestrian interaction. We can learn to obtain the relative importance of the current state and the historical trajectory state as well as the joint impact on the robot's obstacle avoidance strategy. Secondly, the reward function of reinforcement learning is designed based on the spatial behaviour of pedestrians, and the robot is punished for the state where the angle changes too much, so as to achieve the requirement of comfortable obstacle avoidance. Finally, the feasibility and effectiveness of the deep reinforcement learning-based mobile robot obstacle avoidance algorithm in the warehouse environment in the complex environment of the warehouse are verified through simulation experiments. © 2024 IEEE.

关键词： Deep reinforcement learning

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Optimize a novel Integrated Solutions to analyses Privacy persevering of the Internet of things 6

Optimize a novel Integrated Solutions to analyses Privacy pe...

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6th international conference on Information Systems and Computer Networks, ISCON 2023

作者： Mishra, Amit Kumar Tripathi, Neha Bagla, Piyush Pandey, Neeraj Kumar Mittal, Saksham Rana, Deepak Singh Graphic Era Hill University Dept. of Computer Science and Engineering Uttarakhand Dehradun India Graphic Era Deemed to Be University Dept. of Computer Science and Engineering Uttarakhand Dehradun India National Institute of Technology Computer Science and Engineering Dept. Punjab Jalandhar India Dit University School of Computing Uttarakhand Dehradun India Graphic Era Hill University School of Computing Uttarakhand Dehradun India

ISBN: (纸本)9798350346961

Internet of things (IoT) develops a global network of interconnected items or things that will play a significant part in Future Internet (FI). For the IoT to be extensively accepted by individuals and businesses, there must be confidence in the IoT security architecture. It is crucial to establish how IoT devices may connect and share data with one other and with remote servers in an efficient and safe manner. therefore, we provide solutions for IoT environment security and privacy in this paper. Our study begins with the construction of novel three layered approach with Pseudo-Random Number Generators. that after, we have applied a Key Generation Center (KGC) protocol to enable secure multicast group communication in the IoT. A key setup method that ensures the secrecy, authenticity, and integrity of data shared in the network while taking into account the features of IoT devices is one of the IoT security basics. To evaluate the performance of the proposed system, we examine its computational and communication costs.. © 2023 IEEE.

关键词： Internet of things

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Proceedings of international conference on High Performance computing in Asia-Pacific Region, HPC Asia 2023

Proceedings of International Conference on High Performance ...

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6th international conference on High Performance computing in Asia-Pacific Region, HPC Asia 2023

ISBN: (纸本)9781450398060

the proceedings contain 15 papers. the topics discussed include: reducing shared memory footprint to leverage high throughput on tensor cores and its flexible API extension library;efficient large integer multiplication with arm SVE instructions;effectiveness of the oversubscribing scheduling on supercomputer systems;a new data conversion method for mixed precision Krylov solvers with FP16/BF16 Jacobi preconditioners;fault tolerance for ensemble-based molecular-continuum flow simulations;comparison of reproducible parallel preconditioned BiCGSTAB algorithm based on ExBLAS and ReproBLAS;a case study on DaCe portability & performance for batched discrete Fourier transforms;memory usage prediction of HPC workloads using feature engineering and machine learning;and associative operator precedence parsing: a method to increase data parsing parallelism.

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Crop Damage Detection using Machine Learning Approaches 6

Crop Damage Detection using Machine Learning Approaches

引用

6th IEEE international conference on Recent Advances in Intelligent Computational Systems, RAICS 2024

作者： Nair, Priyanka C Sampath, Nalini Reddy, P Praneeth Shruthi, P Sai Department of Computer Science and Engineering Amrita School of Computing Bengaluru India

ISBN: (纸本)9798350381689

Agriculture is of vital importance to human life as it is the main source of livestock production and contributes significantly to the country's employment opportunities and economy. Ensuring high standards of production quality is essential. Recent technological advances are merging agricultural and machine learning techniques to help improve crop quality. the main objective of this work is to make use of machine learning approaches to identify the healthy status of the crop. Multi-class classification is applied to the dataset which helps classify crop conditions. As there is an imbalance of data of the 3 classes, Random under- sampling and Tomek under-sampling methods are applied on the dataset. A combination of Tomek undersampling and Smote undersampling has also been performed on this dataset. Various algorithms like Gradient Boosting, Gaussian Naïve Bayes, Neural Network (MLP) and k-Nearest Neighbors were performed on the dataset which helped show that Randomforest was the best model in terms of accuracy and F1 score. © 2024 IEEE.

关键词： Adversarial machine learning

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An improved PSO algorithm based on stream computing and multi-swarm 6

An improved PSO algorithm based on stream computing and mult...

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6th international conference on Computer Information Science and Application Technology, CISAT 2023

作者： Dai, Likun Wang, Jin Tang, Peiyi Lv, Taizhi College of Information Engineering Jiangsu Maritime Institute Nanjing China Nanjing Huihai Transportation Technology Company Limited Nanjing China

ISBN: (纸本)9781510668546

Due to its simplicity and fast convergence speed, the particle swarm optimization (PSO) algorithm has been applied in many fields to solve various optimization problems. An improved PSO algorithm based on stream computing and multi-swarm is proposed to solve the problem of low efficiency and easy to fall into local optimal solution for the traditional PSO algorithm, and it is abbreviated as SC&MS PSO. In order to solve the problem of premature convergence caused by multimodal functions, this algorithm adopts multi-swarm. In the initial stage, the swarm is divided into several swarms based on the particle characteristics, and each swarm evolves separately, improving the global search ability of particles. Based on stream computing technology, this algorithm executes particle swarm evolving in distributed parallel. the experimental results show that the proposed algorithm not only has a faster convergence rate and more effective global search capability under the unimodal function, but also achieves better experimental results under the complex and deceptive multimodal function, which confirms that stream computing and multi- swarm can effectively improve the performance of the PSO algorithm. © 2023 SPIE.

关键词： Particle swarm optimization (PSO)

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the Internet of things in the Rearing of Giant Freshwater Prawn: A Pilot Study 6

The Internet of Things in the Rearing of Giant Freshwater Pr...

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6th international conference on applied Computational Intelligence in Information Systems, ACIIS 2023

作者： Aziz, Musyaffa' Suhaili, Wida Haji Kumar Patchmuthu, Ravi Shams, Shahriar Universiti Teknologi Brunei School of Computing and Informatics Bandar Seri Begawan Brunei Universiti Teknologi Brunei Faculty of Engineering Bandar Seri Begawan Brunei

ISBN: (纸本)9798350317428

the Internet of things is an advanced technology that connects devices worldwide, making them smart, aware of their surroundings, and able to offer sophisticated services and applications to improve daily activities. this paper reviews the possible sensors and automation needed for giant freshwater prawn rearing and issues that can arise. the Internet of things encompasses the hardware, software, and communication infrastructure that enables real-time monitoring and automation in the rearing of giant freshwater prawn. the features of the system include measuring water quality parameters using sensors, notifying users when the water quality parameter falls below or rises above the optimum value, a historical data set of the water parameters, and manual and conditional actuators. A pilot study was conducted to test the capabilities of the Internet of things on giant freshwater prawn post-larvae. the results of this study suggest that the sensors' readings are 97.6% similar to the manual tests. Despite the noticeable limitations, this study suggests that the potential of the Internet of things in rearing giant freshwater prawn is limitless. the system can effectively monitor water quality parameters, feed consumption, and other environmental parameters. © 2023 IEEE.

关键词： Internet of things

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Evaluating User Interface and User Experience in Mobile Applications Designed for the Elderly 6

Evaluating User Interface and User Experience in Mobile Appl...

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6th international conference on applied Computational Intelligence in Information Systems, ACIIS 2023

作者： Rosman, Syazwan Siau, Nor Zainah Bramantoro, Arif Universiti Teknologi Brunei School of Computing and Informatics Brunei

ISBN: (纸本)9798350317428

the mobile applications have been widely used nowadays, with a growing number of elderly individuals incorporating them into their daily lives. Despite the widespread adoption of smartphones and their associated applications, elderly users often encounter usability challenges. Existing literature suggested that these challenges could be attributed to age-related factors and their relative unfamiliarity with technology, all of which affect their interaction with mobile applications. this research endeavors to identify key attributes of user interface (UI) and user experience (UX) suitable for individuals aged 60 and above in Brunei Darussalam, addressing their specific limitations, and subjecting the UI to analyze based on established principles. Identification of appropriate UI characteristics was conducted through a combination of desk research and interviews with senior citizens. BruHealth, a mobile application focused on disseminating COVID-19 related information and services in Brunei Darussalam, served as a case study, and User-Centered Design Model was adopted to guide the enhanced design and development of its UI. Subsequently, a usability testing was conducted to assess the UI and UX of the improved design, aligning it with heuristic principles. the results reveal several areas necessitating improvement in the UI and UX of the application to align with age-related impairments. © 2023 IEEE.

关键词： User interfaces

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A Framework for Tele-rehabilitation Gaming System 6

A Framework for Tele-rehabilitation Gaming System

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6th international conference on applied Computational Intelligence in Information Systems, ACIIS 2023

作者： Elaklouk, Ahmed M. S. Zuarni Ramli, Ratna Edris, Ibrahim Padilla-Valdez, Nena Jumaily, Adel Al Universiti Teknologi Brunei School of Computing and Informatics Bandar Seri Begawan Brunei Universiti Teknologi Mara Negeri College of Computing Informatics and Mathematics Seremban Malaysia Universiti Teknologi Brunei Centre for Communication Bandar Seri Begawan Brunei Faculty of Engineering University of Technology Brunei Brunei Department of Computer Science and Software Engineering School of Computing University of Western Australia Australia Ensta Bretagne University France

ISBN: (纸本)9798350317428

Brain damage resulting from stroke and traumatic brain injury is the primary cause of complicated disability and one of the major causes of mortality in most countries, burdening healthcare systems owing to the growth in the number of brain injury victims. Rehabilitation is required to deal with the brain damage. With fewer therapists available, it is very challenging to manage patients and even motivate them to participate actively in their rehabilitation. Patients have frequently complained that many traditional rehabilitation systems are monotonous and uninteresting. the study's objective is to propose a telerehabilitation gaming system framework that can serve as guidance for developing an affordable rehabilitation gaming system that can motivate and engage patients and increase rehabilitation effectiveness. the research methodology is based on synthesizing related research and currently available technologies. the proposed framework includes the therapist and patient attached with vital constructs: tailoring tools, instructional content, game characteristics, tailored games, and performance. It is an internet-based communication structure that connects the Rehabilitation Gaming System to the hospital and other care provider networks. the proposed framework is evaluated by a panel of five experts. the results reveal that all experts believe that the proposed framework can serve as a useful guide for creating gaming interventions that can boost the patient's motivation and engagement and increase the effectiveness of rehabilitation. © 2023 IEEE.

关键词： Serious games

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