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Current Status and Prospects of Risk Management Research in the Era of Big Data intelligence 3

Current Status and Prospects of Risk Management Research in ...

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2023 3rd international conference on Big Data, Artificial intelligence and Risk Management, ICBAR 2023

作者： Deng, Renlong Jiang, Jiang Ou, Chaomin Chen, Zhiyu Li, Huiming College of System Engineering National University of Defense Technology Hunan Changsha China

ISBN: (纸本)9798400716478

This study investigates the current status and assesses the prognostications pertaining to the implementation of risk management within the realm of big data intelligence. Research focal points within this domain are scrutinized utilizing bibliometric analysis. The prevailing innovative aspects of risk management during the era of big data intelligence are delineated, and bespoke innovative strategies germane to distinct domains are systematically examined to address the specific exigencies of each field. Common challenges encountered in the domain of big data risk management are deliberated upon, with a comparative analysis of distinct challenges prevalent in diverse fields. A predictive model is formulated to prognosticate the developmental trajectory of literature output in this field over the ensuing two years. Furthermore, prospective avenues for research, including the augmentation of data governance, fostering cross-disciplinary collaboration, and the development of intelligent decision support systems, are posited. These propositions furnish theoretical underpinnings and pragmatic references to advance the innovation and application of risk management within the ambit of big data intelligence. © 2023 ACM.

关键词： Risk management

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AN ELECTROMAGNETIC PULSE COUPLING SIGNAL detection METHOD FOR ENGINE SPEED CONTROL system 3

AN ELECTROMAGNETIC PULSE COUPLING SIGNAL DETECTION METHOD FO...

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3rd international conference on Mechanical, Aerospace and Automotive Engineering, CMAAE 2023

作者： Xu, Zhixin Yu, Yingsong Wei, Minxiang College of Energy and Power Engineering Nanjing University of Aeronautics and Astronautics 29 Yudao Street Nanjing China

ISBN: (纸本)9781839539954

Engine speed is a key parameter of the engine electronic control system. When the speed control system is under electromagnetic pulse (EMP), the speed signals couple with the EMPs to form EMP coupling signals that interfere with the normal operation of the engine. Thus, this article presents an EMP coupling signal detection method for an engine speed control system. First, we conducted irradiation tests to obtain the characteristics of the EMP coupling signal and analyzed the effect on the speed control system. Then, a fitting generation method that transiently mixes multiple sinusoidally damped signals with the speed signal is used to expand the data set. Finally, the detection method based on convolutional neural network (CNN) and Time-frequency analysis is designed, and the acquired signals are made into image sets and fed into the designed convolution neural network for training. The accuracy of the trained model in identifying the EMP coupling signal and the normal speed signal reached 98.5%. © The Institution of Engineering & technology 2023.

关键词： Electromagnetic pulse

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A Scalable Platform to Collect, Store, Visualize and Analyze Big Data in Real- Time 3

A Scalable Platform to Collect, Store, Visualize and Analyze...

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3rd international conference on Innovative Practices in technology and Management, ICIPTM 2023

作者： Kshirsagar, Pravin Ramdas Reddy, Dhoma Harshavardhan Dhingra, Mallika Dhabliya, Dharmesh Gupta, Ankur S B Jain College of Engineering and Technology Department of Artificial Intelligence Maharashtra Nagpur India Trainee Security Analyst JunoClinic Davman Technology Services Private Limited Maharashtra Mumbai India Manipal University Jaipur Department of Mathematics and Statistics Rajasthan Jaipur India Vishwakarma Institute of Information Technology Department of Information Technology Maharashtra Pune India Vaish College of Engineering Department of Computer Science and Engineering Haryana Rohtak India

ISBN: (纸本)9798350336238

Examination and evaluation of sentiment The most popular area for dissecting and extracting knowledge from communication data from many sources, such as Facebook, Instagram, Twitter, Amazon, and so on, is known as mining. It plays a fundamental role in enabling the organizations to work productively on advancing the business system and gaining the most comprehensive understanding of the buyer's feedback on their product. It entails calculating a person's behavior in terms of his buying preferences and then placing yourself in his shoes about the commercial aspect of a relationship. You may think of this component as a situation, person, blog post, or tangible experience. Appraisals, checks, and Reflections created by customers may be divided into smaller, more notable pieces for usage by large businesses. The analysis of comparable purchasing behavior may be used to understand the needs of the customer and foresee future opportunities to assist them. E-business Associations may track the uses and passions associated with their Particulars via this internal assessment and adopt better marketing mechanism to give a tailored shopping experience for their customers, so improving their hierarchical advantage. By using the Programming interface key, Twitter data for this article was collected from Twitter. Similarly, we really want to finish setting up the systems. Additionally, the system supported NLP approaches, thus we wish to implement the calculation as a crucial backslide. The exploratory problems exhibit perfection. © 2023 IEEE.

关键词： Big data

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Navigating the Unseen: Proposing an IoT-Based Smart Shoe with Obstacle detection for the Visually Impaired 3

Navigating the Unseen: Proposing an IoT-Based Smart Shoe wit...

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3rd international conference on Technological Advancements in Computational Sciences, ICTACS 2023

作者： Arora, Kavita Pathak, Sonal Quraishi, Suhail Javed Singh, Anupam Singh, Malikhan Ather, Danish School of Computer Applications Manav Rachna International Institute of Research and Studies Haryana Faridabad India Graphic Era Hill University Department of Computer Science and Engineering Dehradun India BSA College of Engineering & Technology Mathura India Amity University in Tashkent Uzbekistan

ISBN: (纸本)9798350342338

Navigating daily life remains a substantial challenge for the visually impaired, despite technological advancements. This paper presents an IoT-based Smart Shoe equipped with ultrasonic sensors, accelerometers, and gyroscopes to detect obstacles, providing real-time feedback to enhance navigation. The system communicates with a mobile application to offer auditory or haptic alerts, focusing on reliability, comfort, and affordability. Tested across varied terrains and lighting conditions, the prototype showed strong performance and accuracy. Visually impaired participants in trials reported increased mobility and independence. The paper also explores potential integration with navigation tools such as GPS and ethical considerations like user privacy. 'Navigating the Unseen' showcases the potential of technology in creating a more inclusive future for the visually impaired, emphasizing human centered design. © 2023 IEEE.

关键词： Assistive technology Human-Centered Design IoT-Based Smart Shoe Obstacle detection Visually Impaired Navigation

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Framework for the Deployment of Intelligent Smart Cities (ISC) using Artificial intelligence and Software Networking Technologies 3

Framework for the Deployment of Intelligent Smart Cities (IS...

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3rd international conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Mohamed, Nachaat Upadhyay, Ramakant Jakka, Geethamanikanta Rambabu, P.V. Alfurhood, Badria Sulaiman Singh, Devesh Pratap Universiti Sains Malaysia Rabdan Academy UAE Homeland Security Abu Dhabi United Arab Emirates Sanskriti University Department of CSE Mathura Uttar Pradesh India University of the Cumberlands Data Analytics Information Technology United States Civil Engineering Princess Nourah Bint Abdulrahman University College of Computer and Information Sciences Department of Computer Sciences Saudi Arabia

ISBN: (纸本)9798350399264

This article's goals include providing a framework for interpersonal and communication to safeguard welfare services and assess how well the innovation ecosystem is now understood. An essay starts with an overview or description of "urban area"This viewpoint includes neighborhood services, modern amenities, or smart infrastructure. Information and technology, digital operations use, monitoring, and interconnection, amongst other things. The section that follows examines various urban planning concerns, either administration or expansion. Utilizing diverse technologies effectively is made possible by innovative information about towns or an answer to a question concerning high-quality public infrastructure. An innovative method of managing networks is the Software Defined Network (SDN) architecture. Unlike switches in a conventional network computing environment, changes in SDN do not process inbound sachets in the similar means. If no inbound packets are identified after searching the linking tables, they are passed to the control system, the SDN's operating system, for processing. A Spread Denial of Service (DoS) outbreak poses the biggest risk to the cyber security of an SDN *** system or application layers of the disease-ridden devices connected to the system will be the target of the attack. The approach for determining whether incoming packets are contaminated or not is clever machine learning-based, and it is proposed in this paper. In the context of smart cities, the deployment of artificial intelligence (AI) has newly drawn more and more attention. The purpose of this study is to perform a works assessment to examine the role of AI in the various parts of smart towns given the relevance of the topic. This study's technique combines a thorough literature evaluation to find the most pertinent papers with reference system investigation to reveal the subtleties of the subject. The findings of this study highlight the significance of this technology, whic

关键词： Smart city

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IoT-Enabled Environmental intelligence: A Smart Monitoring system 3

IoT-Enabled Environmental Intelligence: A Smart Monitoring S...

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3rd international conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023

作者： Thakare, Yogesh N. Karandikar, Aarti M. Butram, Vicky Rokade, Ashay Wankhade, Utkarsha A. Honade, Shrikant Nagpur India Nagpur India S. B. Jain Institute of Technology Management and Research Department of Electronics & Communication Engineering Nagpur India Prof. Ram Meghe Institute of Technology & Research Department of Electronics & Telecommunication Badnera India Shri Ramdeobaba College of Engineering and Management Department of Electronics Engineering Nagpur India Electronics Engg. CSMSS Chh. Shau College of Engg Aurangabad India

ISBN: (纸本)9798350343632

In recent years, global scientific and engineering departments have recognized their duty to protect the environment and public well-being by addressing environmental contamination. This work, propose an IoT-based system for continuous environmental monitoring that rapidly detects issues, allowing for prompt corrective actions. Authorized bodies receive real-time pollution data, enabling timely intervention. This approach safeguards public health and reduces the risk of natural disasters caused by environmental imbalances. Propose innovative solution integrates cutting-edge IoT technology for real-time environmental monitoring, creating an up-to-date environmental information database for informed decision-making. Proactive pollution control methods further enhance public health protection and act as a preventive measure against environmental disasters, advancing sustainable environmental management through science and engineering. The system employs Arduino UNO board (ATMEGA328/P), four distinct sensors: MQ-2 gas sensor, humidity sensor, temperature sensor (DHTII), ultrasonic sensor (HCSR04), and ESP8266 Wi-Fi module, which transmits data to open IoT API service ThingSpeak, where it is analyzed and stored at central office for further action. © 2023 IEEE.

关键词： environment etc human being IOT pollution smart cities

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A Hybrid Machine Learning Approach to Anomaly detection in Industrial IoT 3

A Hybrid Machine Learning Approach to Anomaly Detection in I...

引用

3rd international conference on Advances in Computing, Communication, Embedded and Secure systems, ACCESS 2023

作者： Jayesh, T.P. Pandiaraj, K. Paul, Arya Chandran, Ranjeesh R Menon, Prasanth P Kalasalingam Academy of Research and Education Department of Electronics and Communication Tamil Nadu Srivilliputhur India Adi Shankara Institute of Engineering and Technology Department of Electronics and Communication Kerala India Kalasalingam Academy of Research and Education Department of Instrumentation and Control Engineering Tamil Nadu Srivilliputhur India

ISBN: (纸本)9798350346169

IIoT is the integration of conventional IoT principles into industrial operations. IIoT has a wide range of practical applications, including but not limited to supply chain management, connected cars, smart grids, smart cities, and smart homes. Regrettably, these systems are increasingly becoming the focus of cybercrime attacks. Machine learning is a promising technology for creating and implementing resilient security measures in IIoT networks. A new and innovative approach to detecting cyberattacks in the IIoT is proposed in this document, through the use of a hybrid machine classifier (HMC). The HMC model is a unique amalgamation of different ML models, such as K-nearest neighbor (KNN), extra trees (ET), gradient boosting (GB), AdaBoost (AB), linear discriminant analysis (LDA), ), naive Bayes (NB), support vector machine (SVM), random forest (RFlinear regression (LR), and classification and regression tree (CART). The DS2OS dataset is used to evaluate the proposed method's effectiveness. Several performance metrics, including recall, precision, accuracy, specificity, F1 score, detection rate, and ROC are used to evaluate the system's performance. The proposed model successfully distinguishes between normal and attack traffic, achieving an accuracy rate of 99.7% and 99.8%, respectively. To evaluate the effectiveness of the proposed method, its performance metrics were compared to those of other advanced attack detection algorithms. The outcomes demonstrated that the proposed model outperformed other ML and DL-based techniques © 2023 IEEE.

关键词： Internet of things

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An Integration of Wireless Communications and Artificial intelligence for Autonomous Vehicles for the Successful Communication to Achieve the Destination 3

An Integration of Wireless Communications and Artificial Int...

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3rd international conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Bhardwaj, Ankit Pattnayak, Jui Prasad Gangodkar, Durga Rana, Arti Shilpa, N. Tiwari, Prashant University of Connecticut The Math Company Department of Computer Science and Engineering StorrsCT United States JIS College of Engineering Computer Science and Engineering India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun India Uttaranchal University Uttaranchal Institute of Technology India SR University Department of Electronics and Communication Engineering Telangana Warangal India GLA University Institute of Business Management Mathura India

ISBN: (纸本)9798350399264

Multiple smart agents interacting with one another is a fundamental component of the IoT, sometimes referred to as social IoT, is the Internet of Things. such knowledgeable beings, like autonomous vehicles and robots, are furnished with powerful machine learning for mobile operation. Although it should go without saying that wireless networking is crucial in these situations, there aren't enough studies on the subject to offer a comprehensive knowledge of multi-Agent networks that operate wirelessly. We examine how wireless communications and multi-Agent systems interact in this essay interact while using disruptive reinforcement learning to model each artificial intelligence agent. The illustrative system is served by autonomous vehicles that drive across Manhattan's streets. As a result of receiving obtaining data via wireless transmission from other actors, the necessity to adapt policy exchange reinforcement learning is the first unique discovery. It is easy to see the benefit of using wireless communication. We also show how communication mistakes might negatively affect system performance. To draw an initial conclusion in favor of adopting small cell infrastructure, Direct vehicle-To-vehicle and vehicle-To-infrastructure communication is provided by multi-Agent systems in contrasted. Finally, using real-Time ALOHA, we investigate Over multi-Agent systems, multiple access communication is possible. Instant ALOHA rejects the retransmission mechanism, in contrast to conventional to assure timely wireless communication contributions to a multi-Agent system's learning process and acceptable performance, one should consider reliable packet delivery via re-Transmit after collisions. © 2023 IEEE.

关键词： Multi agent systems

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Research on Landslide detection in SAR Images Based on Multi-channel Change detection Fusion 3

Research on Landslide Detection in SAR Images Based on Multi...

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2023 3rd international conference on Artificial intelligence and Industrial technology Applications, AIITA 2023

作者： Li, Zengqi Chen, Lifu Long, Fengqi Li, Zhonghao Jin, Haixin School of Electrical and Information Engineering Changsha University of Science and Technology Changsha410114 China

The landslides have resulted in the grave loss of human life and economic damage. Currently, emergency investigations predominantly employ manual field investigations and remote sensing interpretation. Traditional methods for assessing landslides are time-consuming and ineffective for widespread and numerous landslides. In response, many scholars have successfully employed optical remote sensing imagery to extract landslides. Nonetheless, landslide regions are typically accompanied by copious rainfall along with inclement weather conditions, such as cloudy or overcast skies, which limits the observation capabilities of optical remote sensing methods. At this juncture, the advantages of SAR systems that can penetrate clouds, rain, and fog, and work around the clock under any weather conditions are highlighted. This paper proposes a framework using multi-channel SAR images to extract landslides. The framework consists of fused multi-channel change detection images and traditional detection methods, resulting in effective landslide detection. The proposed method was verified in an experiment using landslide data triggered by an earthquake in Milin County, Tibet, on November 17, 2017. © Published under licence by IOP Publishing Ltd.

关键词： Landslides

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Facial Emotional Recognition Using Faster Regional Convolutional Neural Network with VGG16 Feature Extraction Model 3

Facial Emotional Recognition Using Faster Regional Convoluti...

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3rd IEEE international conference on Mobile Networks and Wireless Communications, ICMNWC 2023

作者： Yamsani, Nagendar Jabar, Muhammed Basim Adnan, Myasar Mundher Hussein, A.H.A. Chakraborty, Subhra School of Computer Science and Artificial Intelligence SR University Telangana Warangal India National University of Science and Technology Dhi Qar Iraq The Islamic University Najaf Iraq College of Pharmacy Ahl Al Bayt University Karbala Iraq Nitte Meenakshi Institute of Technology Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798350317022

Facial Emotion Recognition (FER) poses a significant challenge when training deep learning (DL) models like Artificial Neural Network (ANN) and machine learning (ML). The primary issue in FER is the detection of the face, the creation of bounding boxes, and the classification of emotional expressions. This paper proposes the use of Faster Regional Convolutional Neural Network (RCNN) for facial recognition and employs a median filter to filter the image dataset. The model leverages the Facial Emotional Recognition (FER 2013) dataset for training and predicting accurate classifications. The Median Filter is used to eliminate noise in the image, such as Salt and Pepper noise, and data augmentation is utilized to generate synthetic data for addressing minor imbalances in classes. Subsequently, the VGG 16 architecture is implemented for precise feature extraction to reduce complexity in the classification process. This paper, achieved accuracy, precision, recall, specificity, and f1-score values of approximately 78.22%, 75.40%, 80.20%, 85.90%, and 71.40%, respectively, when compared to other classification methods like Convolutional Neural Network, ResNet 50, Divide-And-Conquer-Based learning, and Resnet 18. © 2023 IEEE.

关键词： Artificial Neural Network Convolutional Neural Network Deep Learning Facial Emotion Recognition Median Filter

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